11+ EMC GreenPlum Jobs in Hyderabad | EMC GreenPlum Job openings in Hyderabad

1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Publicis Sapient Overview:

The Senior Associate People Senior Associate L1 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution 

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Job Summary:

As Senior Associate L2 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution

The role requires a hands-on technologist who has strong programming background like Java / Scala / Python, should have experience in Data Ingestion, Integration and data Wrangling, Computation, Analytics pipelines and exposure to Hadoop ecosystem components. You are also required to have hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms.

Role & Responsibilities:

Your role is focused on Design, Development and delivery of solutions involving:

• Data Integration, Processing & Governance

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

• Implement scalable architectural models for data processing and storage

• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time mode

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 5+ years of IT experience with 3+ years in Data related technologies

2.Minimum 2.5 years of experience in Big Data technologies and working exposure in at least one cloud platform on related data services (AWS / Azure / GCP)

3.Hands-on experience with the Hadoop stack – HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline.

4.Strong experience in at least of the programming language Java, Scala, Python. Java preferable

5.Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc

6.Well-versed and working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

Preferred Experience and Knowledge (Good to Have):

# Competency

1.Good knowledge of traditional ETL tools (Informatica, Talend, etc) and database technologies (Oracle, MySQL, SQL Server, Postgres) with hands on experience

2.Knowledge on data governance processes (security, lineage, catalog) and tools like Collibra, Alation etc

3.Knowledge on distributed messaging frameworks like ActiveMQ / RabbiMQ / Solace, search & indexing and Micro services architectures

4.Performance tuning and optimization of data pipelines

5.CI/CD – Infra provisioning on cloud, auto build & deployment pipelines, code quality

6.Cloud data specialty and other related Big data technology certifications

Personal Attributes:

• Strong written and verbal communication skills

• Articulation skills

• Good team player

• Self-starter who requires minimal oversight

• Ability to prioritize and manage multiple tasks

• Process orientation and the ability to define and set up processes

Job Description

Mandatory Requirements 

• Experience in AWS Glue

• Experience in Apache Parquet 

• Proficient in AWS S3 and data lake 

• Knowledge of Snowflake

• Understanding of file-based ingestion best practices.

• Scripting language - Python & pyspark

CORE RESPONSIBILITIES

• Create and manage cloud resources in AWS 

• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 

• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 

• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 

• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.

• Define process improvement opportunities to optimize data collection, insights and displays.

• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 

• Identify and interpret trends and patterns from complex data sets 

• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 

• Key participant in regular Scrum ceremonies with the agile teams  

• Proficient at developing queries, writing reports and presenting findings 

• Mentor junior members and bring best industry practices.

QUALIFICATIONS

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 

• Strong background in math, statistics, computer science, data science or related discipline

• Advanced knowledge one of language: Java, Scala, Python, C# 

• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  

• Proficient with

• Data mining/programming tools (e.g. SAS, SQL, R, Python)

• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)

• Data visualization (e.g. Tableau, Looker, MicroStrategy)

• Comfortable learning about and deploying new technologies and tools. 

• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 

• Good written and oral communication skills and ability to present results to non-technical audiences 

• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus: 

• AWS certification

• Spark Streaming 

• Kafka Streaming / Kafka Connect 

• ELK Stack 

• Cassandra / MongoDB 

• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Job Description

We are looking for an experienced engineer with superb technical skills. Primarily be responsible for architecting and building large scale data pipelines that delivers AI and Analytical solutions to our customers. The right candidate will enthusiastically take ownership in developing and managing a continuously improving, robust, scalable software solutions.

Although your primary responsibilities will be around back-end work, we prize individuals who are willing to step in and contribute to other areas including automation, tooling, and management applications. Experience with or desire to learn Machine Learning a plus.

Skills

• Bachelors/Masters/Phd in CS or equivalent industry experience
• Demonstrated expertise of building and shipping cloud native applications
• 5+ years of industry experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka Streams, Py Spark, and streaming databases like druid or equivalent like Hive
• Strong industry expertise with containerization technologies including kubernetes (EKS/AKS), Kubeflow
• Experience with cloud platform services such as AWS, Azure or GCP especially with EKS, Managed Kafka
• 5+ Industry experience in python
• Experience with popular modern web frameworks such as Spring boot, Play framework, or Django
• Experience with scripting languages. Python experience highly desirable. Experience in API development using Swagger
• Implementing automated testing platforms and unit tests
• Proficient understanding of code versioning tools, such as Git
• Familiarity with continuous integration, Jenkins

Responsibilities

• Architect, Design and Implement Large scale data processing pipelines using Kafka Streams, PySpark, Fluentd and Druid
• Create custom Operators for Kubernetes, Kubeflow
• Develop data ingestion processes and ETLs
• Assist in dev ops operations
• Design and Implement APIs
• Identify performance bottlenecks and bugs, and devise solutions to these problems
• Help maintain code quality, organization, and documentation
• Communicate with stakeholders regarding various aspects of solution.
• Mentor team members on best practices

• Does analytics to extract insights from raw historical data of the organization. 
• Generates usable training dataset for any/all MV projects with the help of Annotators, if needed.
• Analyses user trends, and identifies their biggest bottlenecks in Hammoq Workflow.
• Tests the short/long term impact of productized MV models on those trends.
• Skills - Numpy, Pandas, SPARK, APACHE SPARK, PYSPARK, ETL mandatory. 

Do you have a passion for computer vision and deep learning problems? We are looking for someone who thrives on collaboration and wants to push the boundaries of what is possible today! Material Depot (materialdepot.in) is on a mission to be India’s largest tech company in the Architecture, Engineering and Construction space by democratizing the construction ecosystem and bringing stakeholders onto a common digital platform. Our engineering team is responsible for developing Computer Vision and Machine Learning tools to enable digitization across the construction ecosystem. The founding team includes people from top management consulting firms and top colleges in India (like BCG, IITB), and have worked extensively in the construction space globally and is funded by top Indian VCs.

Our team empowers Architectural and Design Businesses to effectively manage their day to day operations. We are seeking an experienced, talented Data Scientist to join our team. You’ll be bringing your talents and expertise to continue building and evolving our highly available and distributed platform.

Our solutions need complex problem solving in computer vision that require robust, efficient, well tested, and clean solutions. The ideal candidate will possess the self-motivation, curiosity, and initiative to achieve those goals. Analogously, the candidate is a lifelong learner who passionately seeks to improve themselves and the quality of their work. You will work together with similar minds in a unique team where your skills and expertise can be used to influence future user experiences that will be used by millions.

• Extensive knowledge in machine learning and deep learning techniques
• Solid background in image processing/computer vision
• Experience in building datasets for computer vision tasks
• Experience working with and creating data structures / architectures
• Proficiency in at least one major machine learning framework
• Experience visualizing data to stakeholders
• Ability to analyze and debug complex algorithms
• Good understanding and applied experience in classic 2D image processing and segmentation
• Robust semantic object detection under different lighting conditions
• Segmentation of non-rigid contours in challenging/low contrast scenarios
• Sub-pixel accurate refinement of contours and features
• Experience in image quality assessment
• Experience with in depth failure analysis of algorithms
• Highly skilled in at least one scripting language such as Python or Matlab and solid experience in C++
• Creativity and curiosity for solving highly complex problems
• Excellent communication and collaboration skills
• Mentor and support other technical team members in the organization
• Create, improve, and refine workflows and processes for delivering quality software on time and with carefully calculated debt
• Work closely with product managers, customer support representatives, and account executives to help the business move fast and efficiently through relentless automation.

• You’re part of an agile, multidisciplinary team.
• You bring your own unique skill set to the table and collaborate with others to accomplish your team’s goals.
• You prioritize your work with the team and its product owner, weighing both the business and technical value of each task.
• You experiment, test, try, fail, and learn continuously.
• You don’t do things just because they were always done that way, you bring your experience and expertise with you and help the team make the best decisions.

• Strong knowledge of and experience with the functional programming paradigm.
• Experience conducting code reviews, providing feedback to other engineers.
• Great communication skills and a proven ability to work as part of a tight-knit team.

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

• Hands-on experience in Development
• 4-6 years of Hands on experience with Python scripts
• 2-3 years of Hands on experience in PySpark coding. Worked in spark cluster computing technology.
• 3-4 years of Hands on end to end data pipeline experience working on AWS environments
• 3-4 years of Hands on experience working on AWS services – Glue, Lambda, Step Functions, EC2, RDS, SES, SNS, DMS, CloudWatch etc.
• 2-3 years of Hands on experience working on AWS redshift
• 6+ years of Hands on experience with writing Unix Shell scripts
• Good communication skills

Required skill

• Around 6- 8.5 years of experience and around 4+ years in AI / Machine learning space
• Extensive experience in designing large scale machine learning solution for the ML use case,  large scale deployments and establishing continues automated improvement / retraining framework.
• Strong experience in Python and Java is required.
• Hands on experience on Scikit-learn, Pandas, NLTK
• Experience in Handling of Timeseries data and associated techniques like Prophet, LSTM
• Experience in Regression, Clustering, classification algorithms
• Extensive experience in buildings traditional Machine Learning SVM, XGBoost, Decision tree and Deep Neural Network models like RNN, Feedforward is required.
• Experience in AutoML like TPOT or other
• Must have strong hands on experience in Deep learning frameworks like Keras, TensorFlow or PyTorch 
• Knowledge of Capsule Network or reinforcement learning, SageMaker is a desirable skill
• Understanding of Financial domain is desirable skill

 Responsibilities 

• Design and implementation of solutions for ML Use cases
• Productionize System and Maintain those
• Lead and implement data acquisition process for ML work
• Learn new methods and model quickly and utilize those in solving use cases