Data Engineer

3 days ago

New Delhi, India Mphasis Full time

Responsibilities- Automate data quality checks and validation processes using SQL, Python, and data testing frameworks. - Perform reconciliation, integrity, and transformation testing across data platforms. - Work with AWS SageMaker Studio (Unified Studio) for validating ML/data workflows and integrations. - Validate data flows on cloud platforms (AWS, Azure). - Integrate automated data validation into CI/CD pipelines. - Collaborate with development, data engineering, and analytics teams to align on standards, governance, and quality.Qualifications- 4 + years of Experience in Data Engineering.Required Skills- Strong QA background with experience in data quality testing and automation. - Hands-on with Amazon SageMaker Studio (Unified Studio) – must have. - Advanced SQL for reconciliation and validation of large datasets. - Scripting skills in Python (PyTest, PySpark, automation scripts). - Practical experience with cloud data platforms: - AWS (S3, Glue, Redshift, Athena, SageMaker Studio). - Familiarity with data testing frameworks (Great Expectations, dbt tests, QuerySurge). - Knowledge of CI/CD tools (Jenkins, GitHub Actions, Azure DevOps).Preferred Skills- Exposure to BI/reporting validation (Power BI, Tableau, Looker). - Understanding of data governance and metadata management. - Knowledge of big data ecosystems (Spark, Hadoop). - API testing experience for data services.Certifications (Preferred/Plus)- AWS Certification (AWS Certified Data Analytics, AWS Machine Learning Specialty, or Solutions Architect). - Microsoft Azure Data Engineer Associate / Google Cloud Professional Data Engineer. - Snowflake SnowPro Certification. - Sage Maker Certification.

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