Senior Data Engineer/Architect

12 hours ago

Hyderabad, Telangana, India Enable Data Incorporated Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Experience Required: 8+Years

Mode of work: Remote

Skills Required: Azure DataBricks, Eventhub, Kafka, Architecture,Azure Data Factory, Pyspark, Python, SQL, Spark,Copilot Studio , Databricks Lakehouse Platform, its architecture, and its capabilities.

Notice Period : Immediate Joiners/ Permanent/Contract role (Can join within 15th September 2025)

Responsibilities

  • Design, develop, and maintain scalable and robust data solutions in the cloud using Apache Spark and Databricks.
  • Gather and analyse data requirements from business stakeholders and identify opportunities for data-driven insights.
  • Build and optimize data pipelines for data ingestion, processing, and integration using Spark and Databricks.
  • Ensure data quality, integrity, and security throughout all stages of the data lifecycle.
  • Collaborate with cross-functional teams to design and implement data models, schemas, and storage solutions.
  • Optimize data processing and analytics performance by tuning Spark jobs and leveraging Databricks features.
  • Provide technical guidance and expertise to junior data engineers and developers.
  • Stay up to date with emerging trends and technologies in cloud computing, big data, and data engineering.
  • Contribute to the continuous improvement of data engineering processes, tools, and best practices.

Requirements:

  • Bachelors or masters degree in computer science, engineering, or a related field.
  • 10+ years of experience as a Data Engineer with a focus on building cloud-based data solutions.
  • Mandatory skills: Azure DataBricks, Eventhub, Kafka, Architecture, Azure Data Factory, Pyspark, Python, SQL, Spark, EventHub, Copilot Studio
  • Experience contributing to the architecture and design of large-scale distributed systems
  • Strong experience with cloud platforms such as Azure or AWS.
  • Proficiency in Apache Spark and Databricks for large-scale data processing and analytics.
  • Experience in designing and implementing data processing pipelines using Spark and Databricks.
  • Strong knowledge of SQL and experience with relational and NoSQL databases.
  • Experience with data integration and ETL processes using tools like Apache Airflow or cloud-native orchestration services.
  • Good understanding of data modelling and schema design principles.
  • Experience with data governance and compliance frameworks.
  • Excellent problem-solving and troubleshooting skills.
  • Strong communication and collaboration skills to work effectively in a cross-functional team.

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