Data Engineering Lead

Job Description - 8+ years’ experience in hands‑on data engineering, including technical leadership on production platforms - We were looking for stronger hands-on technical depth across areas such as building production-grade data pipelines, data quality and validation, Databricks governance/access management, real-time processing, and data security. - We were looking for practical experience in designing solutions, explaining technical decisions and trade-offs, and solving complex data engineering problems. - Candidates who have influenced design and technical decisions with trade offs and rationale. - Clear, hands-on involvement and ownership across the full lifecycle from design, implementation, testing, Security, Governance, deployment, production support. - Enterprise-scale environments, large data volumes (between 10s to 100s TBs ), - Comfortable working with multiple stakeholders (BAs, Architect, Data Scientist, end user). - Experience providing technical governance (design reviews, standards, delivery assurance) and supporting delivery at pace - Comfortable contributing to estimation and commercial discussions and ensuring solutions are feasible and deliverable - Proven ability to mentor and help develop engineers through coaching, feedback, and structured development support - Strong hands‑on coding skills in Python, Java, or similar languages, with strong SQL capability - Proven experience building and operating batch and streaming pipelines in production - Experience with AWS, Databricks / Spark, and modern data architectures - Hands‑on experience using dbt for transformations and Airflow (or equivalent) for orchestration - Solid understanding of data modelling, data quality, and production data systems - Experience working with relational databases such as Postgres or SQL Server - Familiarity with CI/CD pipelines, testing frameworks, and monitoring / observability tooling