Data Engineer

3 days ago

Bangalore, 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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