GD
Mumbai, MAHARASHTRA, India· Full-time
PythonSQLAWSAzure
GD
Salary not disclosed
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Role overview
Job description
Technologies / Skills: Advanced SQL, Python and associated libraries like Pandas, Numpy etc., Pyspark , Shell scripting, DataModelling, Big data, Hadoop , Hive, ETL pipelines and IaC tools like Terraform etc. Responsibilities: Proven success in communicating with users, other technical teams, and senior management to Collect requirements, describe data modeling decisions and develop data engineering strategy. Ability to work with business owners to define key business requirements and convert to user stories with required technical specifications. Communicate results and business impacts of insight initiatives to key stakeholders to collaboratively solve business problems. Working closely with the overall Enterprise Data & Analytics Architect and Engineering practice leads to ensure adherence with the best practices and design principles. Assures quality, security and compliance require
…About this listing
- Listed from Go Digital Technology Consulting's careers site via Keka · last confirmed on the source 25 Oct 2026
- Posted 20 Apr 2026
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Role market pulse
How Data Engineer demand looks in India
Live jobs
89
Posted 30d
41
30d movement
+7.9%
Remote share
3.4%
Salary listed
10.1%
Salary trend 1Y
Not enough history
What they are looking for
Skills & requirements
Qualification
7 years of relevant IT experience 4+ years of hands-on experience Designing and developing Data Pipelines for Data Ingestion or Transformation using Python (PySpark)/Spark SQL in AWS cloud Experience in design and development of data pipelines and processing of data at scale using technologies like EMR, Kinesis, Kafka, Lambda, Glue, Athena, Redshift, Step Functions. Advanced experience in writing and optimizing efficient SQL queries with Python and Hive handling Large Data Sets in Big-Data Environments Experience in debugging, tunning and optimizing PySpark data pipelines Should have implemented concepts and have good knowledge of Pyspark dataframes, joins, caching, memory management, partitioning, parallelism etc. Understanding of Spark UI, Event Timelines, DAG, Spark config parameters, in order to tune the long running data pipelines. Experience working in Agile implementations Experience with building data pipelines in streaming and batch mode. Experience with Git and CI/CD pipelines to deploy cloud applications Good knowledge of designing Hive tables with partitioning for performance Desired
Department · Technology
Hiring company
Go Digital Technology Consulting
Technology
View the company profile, current openings and hiring details.
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