About Tarento:
Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.
We're proud to be recognized as a Great Place to Work, a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you’ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.
Primary Skill/Mandatory Skill/Must Have:
PySpark / Glue
Experience in AWS Data Engineering / ETL projects.
Very good SQL skills.
Knowledge of Snowflake
Built pipeline for streaming data processing and RDBMS / NoSQL extraction.
Worked on RBMS (AWS RDS), NoSQL (DynamoDB), Streaming (Kafka)
Understanding of Medallion architecture
Working knowledge of Data Lake (using Hudi)
Optional - Reporting exposure
Good to have:
Experience with Apache Airflow or other workflow orchestration tools.
Knowledge of AWS Lambda, Step Functions, and EventBridge.
Hands-on experience with Amazon S3, AWS Glue Data Catalog, and AWS Lake Formation.
Familiarity with Apache Spark optimization and performance tuning.
Experience with CI/CD pipelines using Jenkins, GitHub Actions, or AWS CodePipeline.
Proficiency in Git and version control best practices.
Understanding of Data Governance, Data Quality, and Metadata Management.
Exposure to Terraform or AWS CloudFormation for Infrastructure as Code (IaC).
Knowledge of Docker and containerized deployments.
Experience with Datadog, CloudWatch, or other monitoring and logging tools.
Familiarity with dbt (Data Build Tool) for data transformation.
Exposure to REST APIs and integrating external data sources.
Basic knowledge of Python unit testing and data pipeline testing frameworks.
Experience working in Agile/Scrum environments.
Exposure to Power BI, Tableau, or Amazon QuickSight for reporting and visualization.
Educational Qualifications: B.E/B.Tech
Key Responsibilities:
Design, develop, and optimize ETL/data pipelines using PySpark and AWS Glue.
Build and maintain data ingestion pipelines for batch and real-time streaming data.
Work with AWS services such as RDS, DynamoDB, and other data engineering components.
Develop and optimize complex SQL queries for data transformation and analysis.
Integrate data from relational databases, NoSQL databases, and Kafka streaming platforms.
Implement Medallion architecture and Data Lake solutions using Hudi.
Collaborate with cross-functional teams to ensure high-quality, scalable, and reliable data solutions.
Support data validation, performance tuning, and troubleshooting of data pipelines.
Exposure to reporting and analytics tools is an added advantage.
Required Skills:
Strong hands-on experience with PySpark and AWS Glue.
Experience in AWS Data Engineering and ETL projects.
Excellent SQL programming skills.
Knowledge of SnowflakeKey Responsibilities:
Design, develop, and optimize ETL/data pipelines using PySpark and AWS Glue.
Build and maintain data ingestion pipelines for batch and real-time streaming data.
Work with AWS services such as RDS, DynamoDB, and other data engineering components.
Develop and optimize complex SQL queries for data transformation and analysis.
Integrate data from relational databases, NoSQL databases, and Kafka streaming platforms.
Implement Medallion architecture and Data Lake solutions using Hudi.
Collaborate with cross-functional teams to ensure high-quality, scalable, and reliable data solutions.
Support data validation, performance tuning, and troubleshooting of data pipelines.
Exposure to reporting and analytics tools is an added advantage.
Required Skills:
Strong hands-on experience with PySpark and AWS Glue.
Experience in AWS Data Engineering and ETL projects.
Excellent SQL programming skills.
Knowledge of Snowflake.
Experience with Kafka, AWS RDS, DynamoDB, and data pipeline development.
Good understanding of Medallion architecture and Data Lake concepts using Hudi.
Strong problem-solving and analytical skills.
Good to Have:
Experience with reporting and BI tools.
Knowledge of data warehousing best practices and cloud-native data architectures..
Experience with Kafka, AWS RDS, DynamoDB, and data pipeline development.
Good understanding of Medallion architecture and Data Lake concepts using Hudi.
Strong problem-solving and analytical skills.
Good to Have:
Experience with reporting and BI tools.
Knowledge of data warehousing best practices and cloud-native data architectures.
Location: Bangalore
Mode of Work: 5 Days work from office
