Role Summary & Role Description:

Technical Lead with specific Oracle, PLSQL and design, develop, and optimize data workflows on the Databricks platform. The ideal candidate will have deep expertise in Apache Spark, Pyspark, Python, job orchestration, and CI/CD integration to support scalable data engineering and analytics solutions.  Analyzes, designs, develops and maintains software applications to support business units.

Expected to spend 100 % of the time on hands-on development, design and architecture. Capital Markets Projects experience preferred Provides advanced technical expertise in analyzing, designing, estimating, and developing software applications to project schedule. Oversees systems design and implementation of most complex design components. Creates project plans and deliverables and monitors task deadlines. Oversees, maintains and supports existing software applications. Provides subject matter expertise in reviewing, analyzing, and resolving complex issues. Designs and executes end to end system tests of new installations and/or software prior to release to minimize failures and impact to business and end users. Responsible for resolution, communication, and escalation of critical technical issues. Prepares user and systems documentation as needed. Identifies and recommends Industry best practices. Serves as a mentor to junior staff.

• Acts as a technical lead/mentor for developers in day to day and overall  project areas.
• Ability to lead a team of agile developers.
• Worked in a complex deadline driven projects with minimal supervision. Ability to architect/design/develop with minimum requirements by effectively coordinating activities between business analysts, scrum leads, developers and managers.
• Ability to provide agile status notes on  day to day project tasks.

Key Responsibilities:

• Data Lakehouse Development:
  • Design and implement scalable data Lakehouse solutions using Databricks and Delta Lake.
  • Develop and maintain Delta Lake tables with ACID transactions and schema evolution.
• Data Ingestion & Autoloaders:
  • Build ingestion pipelines using Databricks Autoloader for real-time and batch data.
  • Integrate data from various sources including cloud storage (e.g., ADLS, S3), databases, APIs, and streaming platforms.
• ETL & Data Enrichment:
  • Develop ETL workflows to cleanse, transform, and enrich raw data.
  • Implement business logic and data quality checks to ensure reliability and accuracy.
• Performance Optimization:
  • Optimize Spark jobs for performance and cost-efficiency.
  • Monitor and troubleshoot data pipelines using Databricks tools and logging frameworks.
• Data Access & Governance:
  • Enable secure and governed access to data using Unity Catalog or other access control mechanisms.
  • Collaborate with data analysts and scientists to ensure data availability and usability.
• Collaboration & Documentation:
  • Work closely with cross-functional teams including data architects, analysts, and business stakeholders.
  • Document data models, pipeline designs, and operational procedures.

Technical Skills:

• Design and implement robust ETL pipelines using Databricks notebooks and workflows.
• Strong proficiency in Apache Spark, PySpark, and Databricks.
• Hands-on experience with Delta Lake, Autoloader, and Structured Streaming.
• Proficiency in SQL, Python, and cloud platforms (Azure, AWS, or GCP).
• Experience with ETL frameworks, data modeling, and data warehousing concepts.
• Familiarity with CI/CD, Git, and DevOps practices in data engineering.
• Knowledge of data governance, security, and compliance standards.
• Optimize Spark jobs for performance and cost-efficiency.
• Develop and manage job orchestration strategies using Databricks Jobs and Workflows.
• Monitor and troubleshoot production jobs, ensuring reliability and data quality.
• Implement security and governance best practices including access control and encryption.
• Strong Practical experience using Scrum, Agile modelling and adaptive software development.
• Ability to understand and grasp the big picture of system components.
• Experience building environment and architecture and design guides and architecture and application blueprints.
• Strong understanding of data modeling, warehousing, and performance tuning.
• Excellent problem-solving and communication skills.

Core/Must have skills:

Python, Scala, Spark, Databricks, Oracle, SQL, PLSQL, Python, Scala, Apache Spark, Spark Streaming, CI CD pipeline,

AWS cloud experience

Exposure to real-time data processing and event-driven architectures.

Work Schedule: 12 PM IST to 9 PM (IST)

About State Street

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