Back
Tier-1 brand, common Data Engineer role, and metro location drive high applicant competition.
Core data engineering skills transfer well, but RegTech lineage and compliance requirements increase domain sensitivity moderately.
Explicit 7-year minimum plus required ETL, Databricks, SQL and regulatory data skills make shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and build data ingestion pipelines and data processing capabilities for an enterprise platform supporting regulated workflows.
Implement canonical data models, source-to-target mapping, validation checks, and lineage capture to ensure traceable and governed data.
Develop and maintain data quality checks, reconciliation routines, and metadata structures to support auditable and reliable data processing.
Minimum 7 years of experience in data engineering, ETL/ELT development, data warehousing, or related roles.
Strong SQL skills with hands-on experience using relational databases such as PostgreSQL, SQL Server, Oracle, or MySQL.
Experience designing ingestion pipelines, transformation rules, validation checks, and source-to-target mapping specifications.
Ability to handle structured, semi-structured, and file-based data formats like CSV, JSON, Excel, XML, and Parquet.
Experienced in working collaboratively with architects, backend engineers, AI engineers, QA, and domain specialists in regulated or enterprise data environments.
Capable of supporting data governance with a strong focus on documentation, data lineage, metadata, and auditable processes.
Familiarity with Python, Spark, Databricks, Azure Data Factory, dbt, Airflow or equivalent tools in a complex data engineering context.