Data Analytics Engineer

1 week ago

Hyderabad, Telangana, India Talent Hired-the Job Store Full time ₹ 6,00,000 - ₹ 18,00,000 per year

We are seeking a highly skilled Data Engineer with deep experience in Python, PySpark, Scala, Azure Databricks, SQL Server, NoSQL (Cassandra, etc.), and data streaming technologies. The ideal candidate will design and maintain scalable batch and real-time data pipelines, enabling efficient data ingestion, transformation, and analytics in a cloud environment.

Key Responsibilities

  • Design, develop, and maintain data pipelines (batch and real-time) using PySpark, Scala, and Azure Databricks.
  • Build and optimize data ingestion frameworks integrating streaming and static data sources.
  • Implement real-time data streaming solutions using tools like Apache Kafka, Azure Event Hubs, or Spark Structured Streaming.
  • Develop and deploy ETL/ELT workflows leveraging Azure Data Factory, Databricks, and related Azure data services.
  • Work with SQL Server for relational data storage and NoSQL databases (Cassandra, Cosmos DB, MongoDB, etc.) for semi-structured/unstructured data.
  • Design and maintain scalable data lake and data warehouse architectures in Azure Data Lake and Synapse Analytics.
  • Ensure data quality, security, and governance through proper validation, monitoring, and auditing processes.
  • Collaborate with cross-functional teams including data scientists, analysts, and DevOps — to support analytics and AI workloads.
  • Optimize Spark jobs and pipelines for performance, reliability, and cost efficiency.
  • Implement data versioning, change data capture (CDC), and real-time event-driven architectures where applicable.

Required Skills and Qualifications

  • Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
  • 3+ years of experience in data engineering or a related role.
  • Proficiency in Python and PySpark for distributed data processing.
  • Experience with Scala for Spark development.
  • Hands-on expertise in Azure Databricks, Azure Data Factory, and Azure Data Lake.
  • Strong SQL skills with SQL Server (queries, stored procedures, indexing, tuning).
  • Knowledge of NoSQL databases (Cassandra, Cosmos DB, MongoDB, etc.).

  • Practical experience with data streaming frameworks such as:

  • Apache Kafka, Azure Event Hubs, or AWS Kinesis.

  • Spark Structured Streaming or Flink.

  • Understanding of data modeling, data warehousing, and ETL/ELT principles.

  • Familiarity with data pipeline orchestration, CI/CD, and version control tools (Azure DevOps, Git, etc.).
  • Strong analytical and problem-solving abilities, with excellent communication skills.

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