11+ Stackdriver Jobs in India
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InViz is Bangalore Based Startup helping Enterprises simplifying the Search and Discovery experiences for both their end customers as well as their internal users. We use state-of-the-art technologies in Computer Vision, Natural Language Processing, Text Mining, and other ML techniques to extract information/concepts from data of different formats- text, images, videos and make them easily discoverable through simple human-friendly touchpoints.
TSDE - Data
Data Engineer:
- Should have total 3-6 Yrs of experience in Data Engineering.
- Person should have experience in coding data pipeline on GCP.
- Prior experience on Hadoop systems is ideal as candidate may not have total GCP experience.
- Strong on programming languages like Scala, Python, Java.
- Good understanding of various data storage formats and it’s advantages.
- Should have exposure on GCP tools to develop end to end data pipeline for various scenarios (including ingesting data from traditional data bases as well as integration of API based data sources).
- Should have Business mindset to understand data and how it will be used for BI and Analytics purposes.
- Data Engineer Certification preferred
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Experience in Working with GCP tools like |
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Store : CloudSQL , Cloud Storage, Cloud Bigtable, Bigquery, Cloud Spanner, Cloud DataStore |
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Ingest : Stackdriver, Pub/Sub, AppEngine, Kubernete Engine, Kafka, DataPrep , Micro services |
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Schedule : Cloud Composer |
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Processing: Cloud Dataproc, Cloud Dataflow, Cloud Dataprep |
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CI/CD - Bitbucket+Jenkinjs / Gitlab |
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Atlassian Suite |
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Hiring for Azure Data Engineers.
Location: Bangalore
Employment type: Full-time, permanent
website: www.amazech.com
Qualifications:
B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Electrical or Electronic with good academic background.
Experience and Required Skill Sets:
• Minimum 5 years of hands-on experience with Azure Data Lake, Azure Data Factory, SQL Data Warehouse, Azure Blob, Azure Storage Explorer
• Experience in Data warehouse/analytical systems using Azure Synapse.
Proficient in creating Azure Data Factory pipelines for ETL processing; copy activity, custom Azure development, Synapse, etc.
• Knowledge of Azure Data Catalog, Event Grid, Service Bus, SQL, and Purview.
• Good technical knowledge in Microsoft SQL Server BI Suite (ETL, Reporting, Analytics, Dashboards) using SSIS, SSAS, SSRS, Power BI
• Design and develop batch and real-time streaming of data loads to data warehouse systems
Other Requirements:
A Bachelor's or Master's degree (Engineering or computer-related degree preferred)
Strong understanding of Software Development Life Cycles including Agile/Scrum
Responsibilities:
• Ability to create complex, enterprise-transforming applications that meet and exceed client expectations.
• Responsible for the bottom line. Strong project management abilities. Ability to encourage the team to stick to timelines.
Machine Learning (ML)
Data ScienceRoles & Responsibilities:
-Adopt novel and breakthrough Deep Learning/Machine Learning technology to fully solve real world problems for different industries. -Develop prototypes of machine learning models based on existing research papers.
-Utilize published/existing models to meet business requirements. Tweak existing implementations to improve efficiencies and adapt for use-case variations.
-Optimize machine learning model training and inference time. -Work closely with development and QA teams in transitioning prototypes to commercial products
-Independently work end-to-end from data collection, preparation/annotation to validation of outcomes.
-Define and develop ML infrastructure to improve efficiency of ML development workflows.
Must Have:
- Experience in productizing and deployment of ML solutions.
- AI/ML expertise areas: Computer Vision with Deep Learning. Experience with object detection, classification, recognition; document layout and understanding tasks, OCR/ICR
. - Thorough understanding of full ML pipeline, starting from data collection to model building to inference.
- Experience with Python, OpenCV and at least a few framework/libraries (TensorFlow / Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)
- Years with relevant experience:
5+ -Experience or Knowledge in ML OPS.
Good to Have: NLP: Text classification, entity extraction, content summarization. AWS, Docker.
Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.
Roles & Responsibilities:
Work on implementation of real-time and batch data pipelines for disparate data sources.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.
- Build and maintain an analytics layer that utilizes the underlying data to generate dashboards and provide actionable insights.
- Identify improvement areas in the current data system and implement optimizations.
- Work on specific areas of data governance including metadata management and data quality management.
- Participate in discussions with Product Management and Business stakeholders to understand functional requirements and interact with other cross-functional teams as needed to develop, test, and release features.
- Develop Proof-of-Concepts to validate new technology solutions or advancements.
- Work in an Agile Scrum team and help with planning, scoping and creation of technical solutions for the new product capabilities, through to continuous delivery to production.
- Work on building intelligent systems using various AI/ML algorithms.
Desired Experience/Skill:
- Must have worked on Analytics Applications involving Data Lakes, Data Warehouses and Reporting Implementations.
- Experience with private and public cloud architectures with pros/cons.
- Ability to write robust code in Python and SQL for data processing. Experience in libraries such as Pandas is a must; knowledge of one of the frameworks such as Django or Flask is a plus.
- Experience in implementing data processing pipelines using AWS services: Kinesis, Lambda, Redshift/Snowflake, RDS.
- Knowledge of Kafka, Redis is preferred
- Experience on design and implementation of real-time and batch pipelines. Knowledge of Airflow is preferred.
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
XpressBees – a logistics company started in 2015 – is amongst the fastest growing
companies of its sector. While we started off rather humbly in the space of
ecommerce B2C logistics, the last 5 years have seen us steadily progress towards
expanding our presence. Our vision to evolve into a strong full-service logistics
organization reflects itself in our new lines of business like 3PL, B2B Xpress and cross
border operations. Our strong domain expertise and constant focus on meaningful
innovation have helped us rapidly evolve as the most trusted logistics partner of
India. We have progressively carved our way towards best-in-class technology
platforms, an extensive network reach, and a seamless last mile management
system. While on this aggressive growth path, we seek to become the one-stop-shop
for end-to-end logistics solutions. Our big focus areas for the very near future
include strengthening our presence as service providers of choice and leveraging the
power of technology to improve efficiencies for our clients.
Job Profile
As a Lead Data Engineer in the Data Platform Team at XpressBees, you will build the data platform
and infrastructure to support high quality and agile decision-making in our supply chain and logistics
workflows.
You will define the way we collect and operationalize data (structured / unstructured), and
build production pipelines for our machine learning models, and (RT, NRT, Batch) reporting &
dashboarding requirements. As a Senior Data Engineer in the XB Data Platform Team, you will use
your experience with modern cloud and data frameworks to build products (with storage and serving
systems)
that drive optimisation and resilience in the supply chain via data visibility, intelligent decision making,
insights, anomaly detection and prediction.
What You Will Do
• Design and develop data platform and data pipelines for reporting, dashboarding and
machine learning models. These pipelines would productionize machine learning models
and integrate with agent review tools.
• Meet the data completeness, correction and freshness requirements.
• Evaluate and identify the data store and data streaming technology choices.
• Lead the design of the logical model and implement the physical model to support
business needs. Come up with logical and physical database design across platforms (MPP,
MR, Hive/PIG) which are optimal physical designs for different use cases (structured/semi
structured). Envision & implement the optimal data modelling, physical design,
performance optimization technique/approach required for the problem.
• Support your colleagues by reviewing code and designs.
• Diagnose and solve issues in our existing data pipelines and envision and build their
successors.
Qualifications & Experience relevant for the role
• A bachelor's degree in Computer Science or related field with 6 to 9 years of technology
experience.
• Knowledge of Relational and NoSQL data stores, stream processing and micro-batching to
make technology & design choices.
• Strong experience in System Integration, Application Development, ETL, Data-Platform
projects. Talented across technologies used in the enterprise space.
• Software development experience using:
• Expertise in relational and dimensional modelling
• Exposure across all the SDLC process
• Experience in cloud architecture (AWS)
• Proven track record in keeping existing technical skills and developing new ones, so that
you can make strong contributions to deep architecture discussions around systems and
applications in the cloud ( AWS).
• Characteristics of a forward thinker and self-starter that flourishes with new challenges
and adapts quickly to learning new knowledge
• Ability to work with a cross functional teams of consulting professionals across multiple
projects.
• Knack for helping an organization to understand application architectures and integration
approaches, to architect advanced cloud-based solutions, and to help launch the build-out
of those systems
• Passion for educating, training, designing, and building end-to-end systems.
Job responsibilities
- You will partner with teammates to create complex data processing pipelines in order to solve our clients' most complex challenges
- You will collaborate with Data Scientists in order to design scalable implementations of their models
- You will pair to write clean and iterative code based on TDD
- Leverage various continuous delivery practices to deploy, support and operate data pipelines
- Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available
- Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions
- Create data models and speak to the tradeoffs of different modeling approaches
- Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process
- Assure effective collaboration between Thoughtworks' and the client's teams, encouraging open communication and advocating for shared outcomes
- You have a good understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop
- You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting
- Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions
- You are comfortable taking data-driven approaches and applying data security strategy to solve business problems
- Working with data excites you: you can build and operate data pipelines, and maintain data storage, all within distributed systems
- You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments
- Professional skills
- You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives
- An interest in coaching, sharing your experience and knowledge with teammates
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed
- Presence in the external tech community: you willingly share your expertise with others via speaking engagements, contributions to open source, blogs and more
Amazon Web Services (AWS)Machine Learning (ML)
Pythono Convert machine learning models into APIs for applications accessibility
o Running machine learning tests and experiments
o Implementing appropriate ML algorithms
o Creating machine learning models and retraining systems
o Study and transform data science prototypes
o Design machine learning systems
o Research and implement appropriate ML algorithms and tools
o Train and retrain systems when necessary
o Test and deploy models
o Use AI to empower the company with novel capabilities
o Designing and developing machine learning and deep learning system
o Outstanding analytical and problem-solving skills
• Alexa
o Excellent in Python programming
o Experience with AWS Lamda
o Experience with Alexa skills
o Alexa skill directives
o Excellent in NodeJS programming
o Experience with GCP - Dialog Flow and Actions on Google
o Using built-in intents and developing custom intents
o API integration and Postman knowledge
Python
Scala- We are looking for a Data Engineer to build the next-generation mobile applications for our world-class fintech product.
- The candidate will be responsible for expanding and optimising our data and data pipeline architecture, as well as optimising data flow and collection for cross-functional teams.
- The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimising data systems and building them from the ground up.
- Looking for a person with a strong ability to analyse and provide valuable insights to the product and business team to solve daily business problems.
- You should be able to work in a high-volume environment, have outstanding planning and organisational skills.
Qualifications for Data Engineer
- 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 optimising ‘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.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Looking for a candidate with 2-3 years of experience in a Data Engineer role, who is a CS graduate or has an equivalent experience.
What we're looking for?
- Experience with big data tools: Hadoop, Spark, Kafka and other alternate tools.
- Experience with relational SQL and NoSQL databases, including MySql/Postgres and Mongodb.
- Experience with data pipeline and workflow management tools: Luigi, Airflow.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift.
- Experience with stream-processing systems: Storm, Spark-Streaming.
- Experience with object-oriented/object function scripting languages: Python, Java, Scala.
- Strong Python Coding skills and OOP skills
- Should have worked on Big Data product Architecture
- Should have worked with any one of the SQL-based databases like MySQL, PostgreSQL and any one of
- NoSQL-based databases such as Cassandra, Elasticsearch etc.
- Hands on experience on frameworks like Spark RDD, DataFrame, Dataset
- Experience on development of ETL for data product
- Candidate should have working knowledge on performance optimization, optimal resource utilization, Parallelism and tuning of spark jobs
- Working knowledge on file formats: CSV, JSON, XML, PARQUET, ORC, AVRO
- Good to have working knowledge with any one of the Analytical Databases like Druid, MongoDB, Apache Hive etc.
- Experience to handle real-time data feeds (good to have working knowledge on Apache Kafka or similar tool)
- Python and Scala (Optional), Spark / PySpark, Parallel programming
PythonAmazon Web Services (AWS)3+ years of experience in deployment, monitoring, tuning, and administration of high concurrency MySQL production databases.
- Solid understanding of writing optimized SQL queries on MySQL databases
- Understanding of AWS, VPC, networking, security groups, IAM, and roles.
- Expertise in scripting in Python or Shell/Powershell
- Must have experience in large scale data migrations
- Excellent communication skills.
Python• Responsible for developing and maintaining applications with PySpark
• Contribute to the overall design and architecture of the application developed and deployed.
• Performance Tuning wrt to executor sizing and other environmental parameters, code optimization, partitions tuning, etc.
• Interact with business users to understand requirements and troubleshoot issues.
• Implement Projects based on functional specifications.
Must-Have Skills:
• Good experience in Pyspark - Including Dataframe core functions and Spark SQL
• Good customer communication.
• Good Analytical skills
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