ADF (Azure Data Factory) + Databricks+ Snowflake

Join a high-impact data engineering team where you’ll lead the design and delivery of modern, scalable data platforms powered by Azure Data Factory (ADF) and Databricks. This role blends hands-on engineering with technical leadership—driving robust pipelines, reliable transformations, and production-grade data products that enable analytics and business decision-making. You’ll collaborate closely with stakeholders, architects, and engineers to shape end-to-end solutions, improve performance and cost efficiency, and establish best practices across development and operations. If you enjoy solving complex data challenges, mentoring teams, and building cloud-native solutions with a strong focus on quality, observability, and delivery excellence, this is a great opportunity to grow your leadership footprint while working in a collaborative, learning-focused culture. Technical Requirements: Technology->Cloud Integration->Azure Data Factory (ADF) Technology->Data Engineering->Databricks Technology->Data on Cloud->Snowflake Responsibilities: Key Responsibilities: • Lead end-to-end implementation of data ingestion and orchestration workflows using ADF, including scheduling, dependency management, parameterization, and error handling. • Design and develop scalable data processing pipelines in Databricks using Spark-based transformations for batch and incremental loads. • Build and optimize ELT/ETL patterns integrating Snowflake as a target/source, ensuring performance, reliability, and cost efficiency. • Define data pipeline standards (naming, modularity, reusability) and enforce engineering best practices across the team. • Implement monitoring, alerting, and operational runbooks for production pipelines; drive incident triage and root-cause analysis. • Collaborate with stakeholders to translate requirements into technical designs, estimates, and delivery plans; manage risks and dependencies. • Conduct code reviews, mentor engineers, and guide technical decisions to ensure maintainable and secure solutions. • Improve pipeline performance through tuning, partitioning strategies, and efficient data layout/processing approaches. Minimum Qualifications: • BTECH, MTECH, MCA, or MSC. • 7–9 years of overall experience with strong hands-on expertise in ADF and Databricks for building production-grade data pipelines. • Proven experience designing and supporting reliable ETL/ELT workflows, including scheduling, retries, and failure recovery patterns. • Strong SQL skills and experience working with large datasets and data quality considerations. • Experience collaborating with cross-functional teams and leading technical delivery with ownership mindset. Preferred Skills: Technology->Cloud Integration->Azure Data Factory (ADF),Technology->Data Engineering->Databricks,Technology->Data on Cloud-DataStore->Snowflake