Principal Data Scientist

12 hours ago

Davangere, Karnataka, India beBeeDataEngineer Full time ₹ 1,00,00,000 - ₹ 2,00,00,000

Data Engineering Role

Job Description

This is a pivotal role that involves crafting scalable data pipelines, working with real-time streaming data, and collaborating with cross-functional teams to deliver high-quality solutions.

Key Responsibilities
  • Design, build, and optimize data pipelines and ETL workflows.
  • Manage and process large datasets using Spark, PySpark, and SQL.
  • Build and maintain real-time streaming applications with Spark Streaming/Kafka.
  • Collaborate with data scientists and product teams to integrate AI/ML models into production.
  • Ensure data quality, scalability, and performance in all pipelines.
  • Deploy and manage Spark workloads on cloud platforms (AWS, Azure, GCP, Databricks).
  • Automate testing and deployment of Spark jobs via CI/CD pipelines.
Requirements
  • Bachelor's/Master's degree in Computer Science, Computer Engineering, or related field.
  • Minimum 4 years of professional experience as a Data Engineer.
  • Strong expertise in Python, Spark, PySpark.
  • Hands-on experience with Spark SQL, DataFrames, UDFs, DAG execution.
  • Knowledge of data ingestion tools (Kafka, Flume, Kinesis) and data formats (Parquet, Avro, ORC).
  • Proficiency in Airflow/Prefect for scheduling and orchestration.
  • Familiarity with performance tuning in Spark (partitioning, caching, broadcast joins).
  • Experience deploying on Databricks, AWS EMR, Azure HDInsight, or GCP Dataproc.
  • Exposure to testing and CI/CD for data pipelines (pytest, Jenkins, GitHub Actions).
Technical Skills
  • Spark Core API: RDDs, transformations/actions, DAG execution.
  • Spark SQL: DataFrames, schema optimization, UDFs.
  • Streaming: Structured Streaming, Kafka integration.
  • Data Handling: S3, HDFS, JDBC, Parquet, Avro, ORC.
  • Orchestration: Airflow/Prefect.
  • Performance Tuning: Partitioning, caching, broadcast joins.
  • Cloud Deployment: Databricks, AWS EMR, Azure HDInsight, GCP Dataproc.
  • CI/CD: Pytest/unittest for Spark jobs, Jenkins, GitHub Actions.

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