We are seeking a Lead/Senior Data Engineer to design and build scalable data pipelines, models, and analytics-ready datasets using modern cloud and Databricks-based lakehouse architectures.
Responsibilities
Design, build, and optimize ETL/ELT pipelines using Databricks, Spark, SQL, and Python.
Support migration from legacy data warehouses to modern cloud/lakehouse platforms.
Develop dimensional models, data marts, and curated datasets for analytics and AI use cases.
Collaborate with technical and business stakeholders to translate requirements into solutions.
Ensure data quality, performance, governance, and scalability.
Provide technical guidance and mentorship to other engineers.
Requirements
4–5+ years of data engineering or analytics engineering experience.
Strong SQL and Python skills.
Hands-on Databricks and Spark experience.
Experience with orchestration tools such as Airflow, dbt, or Cloud Composer.
Strong knowledge of data modeling and modern data warehouse/lakehouse architectures.
Excellent communication and stakeholder management skills.
Preferred
Experience with legacy-to-cloud data migrations.
Knowledge of data governance, quality, metadata, and lineage.
Experience supporting analytics or AI/ML initiatives.
