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Tier-1 brand, generalist data-engineer title, mid-level 5+yrs, metro and broad skillset drive high competition.
Core data engineering skills transfer across industries, though ERP/finance domain experience moderately increases fit preference.
Explicit 5+ years plus mandatory AWS/ETL/Databricks/Python/SQL skills create highly strict shortlisting filters.
Design and build data engineering automations including low code/no code solutions to accelerate development cycle time.
Develop and implement ETL jobs, including data profiling, data mapping, and validation to support analytical and reporting solutions.
Manage metadata structures and provide post-deployment support for data science outcomes.
Bachelor's Degree in Computer Science or equivalent.
Minimum 5+ years of hands-on experience in data engineering.
Hands-on experience with AWS services (Redshift, Glue, RDS, Step Functions, S3, SageMaker, Kinesis), SQL on Oracle/MySQL/PostgreSQL, Python, Unix.
Experience in data warehousing, big data, ETL tools (Matillion or Informatica), and handling OLTP and OLAP data models.
Proficient in metadata management, data modeling methodologies, master data management, and data lineage techniques.
Experienced with industrial/commercial data domains including ERP, CRM, finance, and accounting data.
Capabilities to partner with cross-functional teams, drive technical solutions aligned with business outcomes, and communicate project status effectively.