Data Engineer (Databricks)

Project Description: We are seeking a highly skilled Databricks Platform Engineer with strong experience in data engineering. The candidate will have a deep understanding of both data platforms and software engineering, enabling them to effectively integrate and operate the platform within a broader IT ecosystem. This role requires a hands-on individual contributor who takes full ownership of deliverables end-to-end, including design, development, testing, deployment, and ongoing support.

Responsibilities: • Manage and optimize Databricks data platform including workspace setup, cluster policies, job orchestration, Unity Catalog, cost controls, multi-tenancy. • Design, write and maintain APIs used for Platform automation, Serverless workflows, Deployment pipelines, release management and repository management • Ensure high availability, security, and performance of data systems which includes access control, secrets management, RBAC, monitoring, alerting, RLS, incident handling, performance tuning. • Provide valuable insights about the data platform (Databricks) usage which includes cost attribution, usage analytics, workload patterns, telemetry. • Implementing new features of Databricks, including serverless, Declarative Pipelines, Agents, lakebase , etc. • Design and maintain system libraries (Python) used in ETL pipelines and platform governance (Databricks). • Optimize ETL Processes - Enhance and tune existing ETL processes for better performance, scalability, and reliability.

Mandatory Skills Description: • Minimum 10 Years of experience in IT/Data. • Minimum 5 years of experience as a Databricks Data Platform Engineer. • 3+ years of experience in designing, writing, and maintaining APIs used for Platform automation, Serverless workflows, Deployment pipelines, release management and repository management • Bachelor's in IT or related field. • Infrastructure & Cloud: Azure, AWS (expertise in storage, networking, compute). • Programming: Proficiency in PySpark for distributed computing. • minimum 4 years of Python experience for ETL development. • SQL: Expertise in writing and optimizing SQL queries, preferably with experience in databases such as PostgreSQL, MySQL, Oracle, or Snowflake. • Data Warehousing: Experience working with data warehousing concepts and Databricks platform. • ETL Tools: Familiarity with ETL tools & processes • Data Modelling: Experience with dimensional modelling, normalization/denormalization, and schema design. • Version Control: Proficiency with version control tools like Git to manage codebases and collaborate on development. • Data Pipeline Monitoring: Familiarity with monitoring tools (e.g., Prometheus, Grafana, or custom monitoring scripts) to track pipeline performance. • Data Quality Tools: Experience implementing data validation, cleaning, and quality frameworks, ideally Monte Carlo.

Nice-to-Have Skills Description: • Containerization & Orchestration: Docker, Kubernetes. • Infrastructure as Code (IaC): Terraform. • Understanding of Investment Data domain (desired).

Languages: English: C1 Advanced