11+ Quality improvement Jobs in Chennai | Quality improvement Job openings in Chennai
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BASIC QUALIFICATIONS
- 2+ years experience in program or project management
- Project handling experience using six sigma/Lean processes
- Experience interpreting data to make business recommendations
- Bachelor’s degree or higher in Operations, Business, Project Management, Engineering
- 5-10 years' experience in project / Customer Satisfaction, with proven success record
- Understand basic and systematic approaches to manage projects/programs
- Structured problem solving approach to identify & fix problems
- Open-minded, creative and proactive thinking
- Pioneer to invent and make differences
- Understanding of customer experience, listening to customers' voice and work backwards to improve business process and operations
- Certification in 6 Sigma
PREFERRED QUALIFICATIONS
- Automation Skills with experience in Advance SQL, Python, Tableau
PythonAWS Glue Developer
Work Experience: 6 to 8 Years
Work Location: Noida, Bangalore, Chennai & Hyderabad
Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops,
Job Reference ID:BT/F21/IND
Job Description:
Design, build and configure applications to meet business process and application requirements.
Responsibilities:
7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.
Technical Experience:
Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.
➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.
➢ Create data pipeline architecture by designing and implementing data ingestion solutions.
➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.
➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.
➢ Author ETL processes using Python, Pyspark.
➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.
➢ ETL process monitoring using CloudWatch events.
➢ You will be working in collaboration with other teams. Good communication must.
➢ Must have experience in using AWS services API, AWS CLI and SDK
Professional Attributes:
➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.
➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.
➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.
Qualification:
➢ Degree in Computer Science, Computer Engineering or equivalent.
Salary: Commensurate with experience and demonstrated competence
Data AnalyticsTitle: Platform Engineer Location: Chennai Work Mode: Hybrid (Remote and Chennai Office) Experience: 4+ years Budget: 16 - 18 LPA
Responsibilities:
- Parse data using Python, create dashboards in Tableau.
- Utilize Jenkins for Airflow pipeline creation and CI/CD maintenance.
- Migrate Datastage jobs to Snowflake, optimize performance.
- Work with HDFS, Hive, Kafka, and basic Spark.
- Develop Python scripts for data parsing, quality checks, and visualization.
- Conduct unit testing and web application testing.
- Implement Apache Airflow and handle production migration.
- Apply data warehousing techniques for data cleansing and dimension modeling.
Requirements:
- 4+ years of experience as a Platform Engineer.
- Strong Python skills, knowledge of Tableau.
- Experience with Jenkins, Snowflake, HDFS, Hive, and Kafka.
- Proficient in Unix Shell Scripting and SQL.
- Familiarity with ETL tools like DataStage and DMExpress.
- Understanding of Apache Airflow.
- Strong problem-solving and communication skills.
Note: Only candidates willing to work in Chennai and available for immediate joining will be considered. Budget for this position is 16 - 18 LPA.
JavaPythonData Engineer- Senior
Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.
What are you going to do?
Design & Develop high performance and scalable solutions that meet the needs of our customers.
Closely work with the Product Management, Architects and cross functional teams.
Build and deploy large-scale systems in Java/Python.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Create data tools for analytics and data scientist team members that assist them in building and optimizing their algorithms.
Follow best practices that can be adopted in Bigdata stack.
Use your engineering experience and technical skills to drive the features and mentor the engineers.
What are we looking for ( Competencies) :
Bachelor’s degree in computer science, computer engineering, or related technical discipline.
Overall 5 to 8 years of programming experience in Java, Python including object-oriented design.
Data handling frameworks: Should have a working knowledge of one or more data handling frameworks like- Hive, Spark, Storm, Flink, Beam, Airflow, Nifi etc.
Data Infrastructure: Should have experience in building, deploying and maintaining applications on popular cloud infrastructure like AWS, GCP etc.
Data Store: Must have expertise in one of general-purpose No-SQL data stores like Elasticsearch, MongoDB, Redis, RedShift, etc.
Strong sense of ownership, focus on quality, responsiveness, efficiency, and innovation.
Ability to work with distributed teams in a collaborative and productive manner.
Benefits:
Competitive Salary Packages and benefits.
Collaborative, lively and an upbeat work environment with young professionals.
Job Category: Development
Job Type: Full Time
Job Location: Bangalore
Responsibilities:
• Designing Hive/HCatalog data model includes creating table definitions, file formats, compression techniques for Structured & Semi-structured data processing
• Implementing Spark processing based ETL frameworks
• Implementing Big data pipeline for Data Ingestion, Storage, Processing & Consumption
• Modifying the Informatica-Teradata & Unix based data pipeline
• Enhancing the Talend-Hive/Spark & Unix based data pipelines
• Develop and Deploy Scala/Python based Spark Jobs for ETL processing
• Strong SQL & DWH concepts.
Preferred Background:
• Function as integrator between business needs and technology solutions, helping to create technology solutions to meet clients’ business needs
• Lead project efforts in defining scope, planning, executing, and reporting to stakeholders on strategic initiatives
• Understanding of EDW system of business and creating High level design document and low level implementation document
• Understanding of Big Data Lake system of business and creating High level design document and low level implementation document
• Designing Big data pipeline for Data Ingestion, Storage, Processing & Consumption
The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
Responsibilities for Data Engineer
• 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.
• 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.
Qualifications for Data Engineer
• Experience building and optimizing big data ETL pipelines, architectures and data sets.
• Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
• 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.
Experience – 3 – 12 yrs
Budget - Open
Location - PAN India (Noida/Bangaluru/Hyderabad/Chennai)
Presto Developer (4)
Understanding of distributed SQL query engine running on Hadoop
Design and develop core components for Presto
Contribute to the ongoing Presto development by implementing new features, bug fixes, and other improvements
Develop new and extend existing Presto connectors to various data sources
Lead complex and technically challenging projects from concept to completion
Write tests and contribute to ongoing automation infrastructure development
Run and analyze software performance metrics
Collaborate with teams globally across multiple time zones and operate in an Agile development environment
Hands-on experience and interest with Hadoop
- 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.
Python
Django- Analyze and organize raw data
- Build data systems and pipelines
- Evaluate business needs and objectives
- Interpret trends and patterns
- Conduct complex data analysis and report on results
- Build algorithms and prototypes
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
- Should have 5+ years of experience as a data engineer or in a similar role
- Technical expertise with data models, data mining, and segmentation techniques
- Should have experience programming languages such as Python
- Hands-on experience with SQL database design
- Great numerical and analytical skills
- Degree in Computer Science, IT, or similar field; a Master’s is a plus
- Data engineering certification (e.g. IBM Certified Data Engineer) is a plus
Machine Learning (ML)
Data SciencePythonWork Location : Chennai
Experience Level : 5+yrs
Package : Upto 18 LPA
Notice Period : Immediate Joiners
It's a full-time opportunity with our client.
Mandatory Skills:Machine Learning,Python,Tableau & SQL
Job Requirements:
--2+ years of industry experience in predictive modeling, data science, and Analysis.
--Experience with ML models including but not limited to Regression, Random Forests, XGBoost.
--Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models.
--Experience writing code in Python and SQL with documentation for reproducibility.
--Strong Proficiency in Tableau.
--Experience handling big datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL.
--Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
--AWS Sagemaker experience is a plus not required.
Responsibilities for Data Engineer
- 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.
Qualifications for Data Engineer
- 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.
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