Job DescriptionJoin a high-impact data engineering team where youll 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 leadershipdriving robust pipelines, reliable transformations, and production-grade data products that enable analytics and business decision-making. Youll 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.

Roles ResponsibilitiesKey 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 effective data layout/processing approaches.

Minimum Qualifications

- BTECH, MTECH, MCA, or MSC.
- 79 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 RequirementTechnology->Cloud Integration->Azure Data Factory (ADF)

Technology->Data Engineering->Databricks

Technology->Data on Cloud->Snowflake

Additional ResponsibilityPreferred 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.

Educational

RequirementMCA,MSc,MTech,Bachelor of Engineering,BTech

Preferred SkillsTechnology->Cloud Integration->Azure Data Factory (ADF),Technology->Data Engineering->Databricks,Technology->Data on Cloud-DataStore->Snowflake

Service LineData Analytics Unit

📌 ADF (Azure Data Factory) + Databricks+ Snowflake (Bengaluru)
🏢 Infosys
📍 Bengaluru