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Quantiphi - Senior Data Engineer - ETL / Azure Databricks

Quantiphi - Senior Data Engineer - ETL / Azure Databricks

Quantiphi AnalyticsMumbai
12 days ago
Job description

While technology is the heart of our business, a global and diverse culture is the heart of our success.

We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests youyou would enjoy your career with Quantiphi!.

Role : Senior Data Engineer (Databricks).

Experience Level : 3 to 6 Years.

Work location : Mumbai, Bengaluru, Trivandrum.

Role & Responsibilities :

  • Design and implement data solutions (ETL pipelines, Processing and Transformation logic) using Snowflake as a key platform.
  • Design Virtual warehouses which are optimized for performance and cost (auto scaling, idle time etc).
  • Write SQL , stored procedures to implement business logic, other critical requirements like encryption, data masking etc.
  • Implement solutions with features like Snowpipe, tasks, streams,dynamic tables etc.
  • Design the solutions by leveraging key concepts around the architecture of Snowflake, its data distribution and partitioning mechanism, data caching etc.
  • Identify queries which take more time , look at the logs etc and provide solutions to optimize those queries.

Must Have Skills :

  • 3+ years experience of Hands-on in data structures, distributed systems, Spark, SQL, PySpark, NoSQL Databases.
  • Strong software development skills in at least one of : Python, Pyspark or Scala.
  • Develop and maintain scalable & modular data pipelines using databricks & Apache Spark.
  • Experience building and supporting large-scale systems in a production environment.
  • Experience working on either of the cloud storages AWS S3, Azure data lake, GCS buckets.
  • Exposure to the ELT tools offered by the cloud platforms like, ADF, AWS Glue, Google dataflow.
  • Integrate Databricks with other cloud services like AWS, Azure or Google Cloud.
  • Implement and optimize Spark jobs, data transformations, and data processing workflows in Databricks.
  • Managing and configuring databricks environments, including clusters and notebooks.
  • Experience working with different file formats parquet, databricks delta lake.
  • Experience working with data governance on databricks, implementing unity catalog, delta share.
  • (ref : hirist.tech)

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