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Mid-tier brand, metro location, popular data-engineer role but senior level and cloud specificity moderate competition.
Core data engineering skills across clouds transfer well across industries.
Explicit 7–10 years requirement and mandatory multi‑cloud and tool experience enforce strict screening.
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Design, develop, and maintain scalable, secure data pipelines and platforms on AWS, Azure, and GCP clouds.
Lead technical solution design, support pre-sales activities with demos and PoCs, and collaborate with architects and stakeholders.
Guide and mentor junior data engineers, enforce best coding practices, and ensure data governance, security, and compliance.
6 to 10 years of data engineering and development experience.
Hands-on expertise with at least two cloud platforms among AWS, Azure, and GCP, including services like BigQuery, Synapse, Redshift, or Databricks.
Strong programming skills in Python and SQL, with experience in ETL/ELT pipelines, data modeling, and modern data architectures.
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
Experienced technical lead comfortable working independently on complex cloud data engineering challenges and collaborating cross-functionally.
Strong background in cloud-based data warehousing, lakehouse architectures, and SaaS data platforms (e.g., Databricks, Snowflake).
Familiar with implementing data governance, security, compliance, and master data management solutions; skilled in performance and cost optimization of cloud data platforms.