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Senior and niche finance-data stack but metro Gurgaon increases applicant interest.
Strong financial-domain and BigQuery/dbt specialization reduces cross-industry transferability.
Explicit 9+ years, financial-domain experience and specific tooling (dbt, BigQuery, Airflow) enforce strict filters.
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Design, build, and maintain scalable ELT pipelines and data models for large-scale financial datasets using dbt, BigQuery, and Apache Airflow on Google Cloud Platform.
Implement data quality, reconciliation, and monitoring processes to ensure accuracy and reliability of financial data pipelines.
Collaborate across teams to translate business requirements into robust cloud-native data platform solutions with operational ownership over pipeline health, performance, and enhancements.
9+ years of experience in data engineering, database development, or related roles.
Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
Hands-on expertise with Python and SQL, along with experience in dbt, BigQuery (or similar cloud data warehouses), and Apache Airflow workflow orchestration.
Experience in financial services or fintech domain working with securities master data, corporate actions, or market data vendor feeds.
Proven ability to design complex data models applying dimensional modeling, slowly changing dimensions, and balance analytical performance with maintainability.
Skilled in creating reliable, idempotent data pipelines with strong focus on data quality, pipeline recovery, and observability in a cloud-native environment.
Experienced in collaborative, cross-functional teams delivering modernised data platforms for financial datasets, with operational accountability and continuous improvement mindset.