Data bricks Lead Data Engineer - R01565550

Lead Data Engineer Primary Skills ETL Fundamentals, SQL, SQL (Basic + Advanced), Python, Data Warehousing, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures Specialization Databricks Engineering: Data Engineer Job requirements Job Description – Data Engineer (Databricks) Company: Aperture Cloud Technologies Role: Data Engineer – Databricks Experience: 5–10 Years Location: India (Hybrid/3 days) Employment Type: Full-time About Aperture Cloud Aperture Cloud is a leading digital transformation partner delivering innovative solutions across Data, Cloud, AI, and Digital Engineering. We help global enterprises unlock value through cutting-edge technology and data-driven insights. Role Overview We are looking for a hands-on Data Engineer with strong Databricks expertise to design, build, and scale modern data platforms. The ideal candidate will have experience in PySpark, Delta Lake, and cloud-native data engineering and will work closely with analytics, product, and business teams to deliver high-performance data pipelines. Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and PySpark Build and optimize data lakehouse architectures (Bronze–Silver–Gold layers) Develop data ingestion frameworks from multiple sources (batch & real-time) Implement Delta Lake features including schema evolution, ACID transactions, and optimization Create and manage Databricks notebooks, workflows, and jobs for production pipelines Ensure data quality, governance, and lineage across pipelines Optimize Spark jobs for performance (partitioning, caching, tuning) Collaborate with cross-functional teams (Data Scientists, Analysts, Architects) Support production deployments, monitoring, and troubleshooting of data pipelines Contribute to migration of legacy data platforms to modern cloud-based architecture Technical Skills (Must-Have) Strong experience in: Databricks (Workflows, Notebooks, Jobs) PySpark / Spark SQL SQL & Data Warehousing concepts Hands-on experience with: Delta Lake / Lakehouse architecture Data pipeline development & orchestration Good understanding of: Data modeling, ETL/ELT processes, SCD concepts Cloud & Tools Experience in at least one: AWS (S3, Glue, EMR) / Azure (ADF, ADLS, Synapse) Workflow tools: Airflow / Databricks Workflows Version control: Git / CI-CD pipelines Good to Have Experience with: Streaming frameworks (Kafka / Spark Streaming) DBT / Snowflake / Redshift / Fabric Exposure to: Unity Catalog, Autoloader, Delta Live Tables Experience Required 5–10 years of experience in Data Engineering Minimum 2–4 years of hands-on Databricks experience Proven experience building enterprise-scale data platforms and pipelines Soft Skills Strong problem-solving and analytical skills Ability to work in a fast-paced, agile environment Good communication and stakeholder management Why Join Aperture Cloud Work on cutting-edge data & AI programs Opportunity to build large-scale data platforms Collaborative and innovation-driven culture We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.