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.

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.

Technical requirements

Technology->Cloud Integration->Azure Data Factory (ADF)

Technology->Data Engineering->Databricks

Technology->Data on Cloud->Snowflake

Additional responsibilities

Preferred Qualifications:

• Strong experience integrating and optimizing workloads with Snowflake, including loading strategies and performance tuning.
• Experience implementing medallion/lakehouse-style architectures and scalable data modeling patterns for analytics consumption.
• Familiarity with CI/CD practices for data engineering workflows and automated testing approaches for pipelines.
• Experience with production observability practices (pipeline metrics, logging, alerting) and operational excellence.
• Demonstrated ability to mentor team members, drive design discussions, and influence engineering standards across projects.

Preferred skills

• Technology › Cloud Integration › Azure Data Factory (ADF)
• Technology › Data Engineering › Databricks
• Technology › Data on Cloud-DataStore › Snowflake

About the role

• Role: Technical Lead
• Experience: 7 - 9 years
• Education: MCA, MSc, MTech, Bachelor of Engineering, BTech