Associate Data Architect II

2 days ago

Thiruvananthapuram, Kerala, India UST Full time

Key Accountabilities / Responsibilities:

  • Provide technical direction and leadership to data engineers on data platform initiatives - ensuring adherence to best practices in data modelling, End to End pipeline design, and code quality.
  • Review and optimize PySpark, SQL, and Databricks code for performance, scalability, and maintainability.
  • Offer engineering support and mentorship to data engineering teams within delivery squads, guiding them in building robust, reusable, and secure data solutions.
  • Collaborate with architects to define data ingestion, transformation, and storage strategies leveraging Azure services such as Azure Data Factory, Azure Databricks, Azure Data Lakes
  • Drive automation and CI/CD practices in data pipelines using tools such as Git, Azure DevOps, and DBT (good to have).
  • Ensure optimal data quality and lineage by implementing proper testing, validation, and monitoring mechanisms within data pipelines.
  • Stay current with evolving data technologies, tools, and best practices, continuously improving standards, frameworks, and engineering methodologies.
  • Troubleshoot complex data issues, analyse system performance, and provide solutions to development and service challenges.
  • Coach, mentor, and support team members through knowledge sharing sessions, technical reviews.

Required Skills & Experience:

  • Developer / engineering background of large-scale distributed data processing systems (or experience in equal measure). Can provide constructive feedback based on knowledge.

  • Proficient in designing scalable and efficient data models tailored for analytical and operational workloads, ensuring data integrity and optimal query performance.

  • Practical experience implementing and managing Unity Catalog for centralized governance of data assets across Databricks workspaces, including access control, lineage tracking, and auditing.

  • Demonstrated ability to optimize data pipelines and queries using techniques such as partitioning, caching, indexing, and adaptive execution strategies to improve performance and reduce costs.

  • Programming in Pyspark (Must), SQL(Must), Python (Good to have).

  • Experience with Databricks (Mandatory) and DBT (Good to have) is required

  • Implemented cloud data technologies on either Azure (Must) other optional GCP, Azure or AWS.

  • Knowledge around shortening development lead time and improving data development lifecycle

  • Worked in an Agile delivery framework.

Required Skills

Pyspark, SQL, Azure Databricks, AWS

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