Role: Data Engineer (Fulltime role)

Location- Bhubaneshwar

Education: Bachelors or Masters degree in Computer Science, Information Technology.

+ What are we looking for?

We are looking for a skilled and motivated Data Engineer with 3 to 5 years of experience in data engineering, data pipelines, data warehousing, and cloud data platforms. The ideal candidate should have strong hands-on experience in building scalable data pipelines, working with large datasets, and implementing data solutions on cloud platforms such as AWS and Azure using tools like Azure Data Factory and Databricks.

This role is ideal for candidates who can independently build and manage data pipelines, support analytics platforms, and contribute to data architecture and data platform development.

Experience:

- 3 to 7 years of experience in Data Engineering, ETL/ELT development, data platform development, or data warehousing projects.
- Hands-on experience in building and maintaining production data pipelines.
- Experience working with cloud data platforms such as AWS or Azure.

• Experience working with large datasets and distributed data processing frameworks.

Technical Expertise:

- Strong knowledge of SQL and database performance tuning.
- Solid programming skills in Python and/or PySpark.
- Experience in building ETL/ELT pipelines and data workflows.
- Strong understanding of data warehousing concepts and data modelling (Star Schema, Snowflake Schema, Data Vault basic understanding).
- Experience working with structured, semi-structured, and unstructured data.
- Understanding of data lakes, data warehouses, and lakehouse architecture.
- Experience in data quality frameworks, data validation, and reconciliation processes.
- Knowledge of batch and streaming data processing.
- Experience in data partitioning,



indexing, and performance optimization.

• Understanding of metadata management and data governance concepts.

Frameworks & Tools:

- Strong hands-on experience with Azure Data Factory or AWS Glue for data integration.
- Hands-on experience with Databricks and PySpark for data processing and transformation.
- Experience working with Azure Data Lake / AWS S3.
- Experience with data warehouses such as Azure Synapse, Redshift, Snowflake, or Databricks SQL.
- Experience with workflow orchestration tools and pipeline scheduling.
- Experience in data ingestion from APIs, databases, files, and streaming platforms.
- Experience with version control tools such as Git.
- Basic experience with CI/CD pipelines and deployment automation.

• Familiarity with monitoring and logging tools for data pipelines.

Additional Knowledge:

- Experience with big data technologies such as Hadoop and Spark.
- Familiarity with streaming technologies such as Kafka, Kinesis, or Azure Event Hub.
- Understanding of data governance, data security, masking, and access control.
- Exposure to infrastructure-as-code tools is an added advantage.

• Understanding of data platform architecture and best practices.

Preferred Qualification:

- Relevant certifications in Azure, AWS, Databricks, or Data Engineering.
- Experience working on end-to-end data platform or data lake implementation projects.




- Contributions to GitHub projects, technical blogs, or internal accelerators/frameworks.

• Experience working in Agile or DevOps environments.

Soft Skills:

- Strong analytical and problem-solving abilities.
- Ability to design and troubleshoot complex data pipelines.
- Good communication and documentation skills.
- Ability to work independently and mentor junior engineers.
- Ability to work with cross-functional teams including data analysts, data scientists, and business teams.

• Strong ownership and accountability.

You would be responsible for:

- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
- Build and optimize data ingestion pipelines from multiple data sources.
- Develop data transformation logic using SQL, Python, and PySpark.
- Work with Azure Data Factory, AWS Glue, and Databricks for data engineering workloads.
- Load and transform data into data lakes and data warehouses.
- Implement data modelling and schema design for analytics and reporting systems.
- Implement data quality checks, validation frameworks, and monitoring.
- Optimize data pipelines for performance, scalability, and reliability.
- Support and maintain production data pipelines and troubleshoot issues.
- Work on cloud-based data platforms on AWS and Azure.
- Collaborate with data analysts, data scientists, visualization teams, and business teams.
- Implement data governance, data security, and access control policies.
- Maintain technical documentation, data dictionaries, and pipeline documentation.
- Mentor junior data engineers and support technical guidance.

• Stay updated with the latest developments in data engineering, big data, and cloud data platforms.

📌 Data Engineer (Bhubaneswar)
🏢 Talent Hired-the Job Store
📍 Bhubaneswar