Azure Databricks Data Engineer

Job description

**About the Company** Greetings from Tata Consultancy Services Recruitment Team! **About the Role** **For all those Azure Databricks Data Engineer we are coming bigger with the plan of Face to Face Drive on 11th July, 2026 (Saturday) in Vishakhapatnam. It is a Face to Face interview planned to attract great Talents in Azure Databricks Data Engineer. We believe that your skills and expertise are a better match for the skills we are looking for.** **Responsibilities** - Databricks: In-depth knowledge of Databricks, Spark, Delta Lake, and related technologies. - Programming: Strong programming skills in Python, Scala, or Java. - Data Engineering: Experience with data engineering, data warehousing, and ETL tools. - Expertise in SQL, Unity Catalogue, Workflows/Jobs. - Data Science: Experience with data science, machine learning, and statistical modeling. - Communication: Excellent communication and collaboration skills. - Cloud Experience: Experience with cloud-based data platforms, such as AWS, Azure, or Google Cloud. - Basic knowledge of machine learning pipelines in Databricks (MLflow, Spark MLlib). - Hands-on experience with Databricks platform, including: - PySpark / Spark SQL for data processing and transformation. - Delta Lake for ACID-compliant data storage. - Notebooks for workflow orchestration and collaborative development. - Strong programming skills in Python and SQL. - Experience in data ingestion from batch and streaming sources. - Knowledge of ETL/ELT design patterns and data pipeline optimization. - Familiarity with cloud data storage and compute environments (AWS, Azure, or GCP). - Basic understanding of workflow orchestration tools (Airflow, Databricks Jobs). - Exposure to DevOps concepts, CI/CD pipelines, and version control (Git). - Awareness of data security, access control, and compliance considerations. - Understanding of performance tuning, partitioning, and caching strategies in Spark. - Hands-on experience in developing, maintaining, and optimizing data pipelines using Databricks. - Knowledge of ETL/ELT pipelines, data ingestion, transformation, and orchestration. - Exposure to data lake, data warehouse, or lakehouse architectures. - Experience with data migration, integration, and automation. - Collaboration with senior engineers, architects, and analytics teams for solution delivery. - Familiarity with security, access control, and compliance best practices. - Working experience in Agile and DevOps environments. **Requirement** - **Years of experience: 5 to 12 Years** - **Location: Vishakhapatnam** - **Date: 11th July, 2026 (Saturday) (Face to Face)** - **Drive Time: 9AM to 2 PM**