Data Engineer - Azure Databricks

Role Overview :

We are seeking a seasoned Data Engineer to join our high-performing data team in Gurgaon. In this role, you will be responsible for architecting, building, and maintaining robust data pipelines that power our analytical ecosystem. You will collaborate closely with cross-functional teams, including data scientists, product managers, and business stakeholders, to transform raw data into actionable insights. Your work will directly influence strategic decision-making and enhance the scalability of our data infrastructure, ensuring that our business remains data-driven and competitive in a fast-paced market.

Key Responsibilities :

• Design and implement scalable ETL/ELT pipelines to integrate disparate data sources, ensuring high data quality and availability for downstream analytics.

• Develop and optimize complex data models within Snowflake and Databricks environments to support high-performance reporting and business intelligence requirements.

• Collaborate with engineering teams to build and maintain secure API integrations, facilitating seamless data flow across our cloud-based architecture.

• Monitor and tune data warehouse performance in Snowflake and BigQuery to reduce latency and optimize cloud infrastructure costs for the organization.

• Partner with stakeholders to translate complex business requirements into technical specifications, ensuring that data solutions align with long-term organizational goals.

Required Skillset :

• Demonstrated expertise in building end-to-end data solutions using Snowflake DB and Azure Databricks, with a deep understanding of modern data warehousing principles.

• Advanced proficiency in SQL for complex query optimization and data manipulation, alongside a strong command of cloud platforms including AWS and GCP.

• Proven ability to design efficient data models that support large-scale analytical workloads and evolving business needs.

• Exceptional communication skills with the ability to articulate technical concepts to non-technical stakeholders and foster collaboration across global teams.

• Strong analytical mindset with a track record of solving complex data engineering challenges in a hybrid work environment.

• A Bachelor's or Master's degree in Computer Science, Information Technology, or a related quantitative field, reflecting a strong foundation in data architecture.