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Data Engineer

5 years

0 Lacs

Pune, Maharashtra, India

Posted:4 days ago| Platform: Linkedin logo

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Skills Required

data databricks engineering design analytics reporting integrity efficiency security governance compliance architecture apache spark programming python scala azure aws gcp sql analysis etl workflow orchestration airflow adf processing kafka learning model deployment agile

Work Mode

On-site

Job Type

Full Time

Job Description

Job Title: Data Engineer – Databricks, Delta Live Tables, Data Pipelines Location: Bhopal / Hyderabad / Pune (On-site) Experience Required: 5+ Years Employment Type: Full-Time Job Summary: We are seeking a skilled and experienced Data Engineer with a strong background in designing and building data pipelines using Databricks and Delta Live Tables. The ideal candidate should have hands-on experience in managing large-scale data engineering workloads and building scalable, reliable data solutions in cloud environments. Key Responsibilities: Design, develop, and manage scalable and efficient data pipelines using Databricks and Delta Live Tables . Work with structured and unstructured data to enable analytics and reporting use cases. Implement data ingestion , transformation , and cleansing processes. Collaborate with Data Architects, Analysts, and Data Scientists to ensure data quality and integrity. Monitor data pipelines and troubleshoot issues to ensure high availability and performance. Optimize queries and data flows to reduce costs and increase efficiency. Ensure best practices in data security, governance, and compliance. Document architecture, processes, and standards. Required Skills: Minimum 5 years of hands-on experience in data engineering . Proficient in Apache Spark , Databricks , Delta Lake , and Delta Live Tables . Strong programming skills in Python or Scala . Experience with cloud platforms such as Azure , AWS , or GCP . Proficient in SQL for data manipulation and analysis. Experience with ETL/ELT pipelines , data wrangling , and workflow orchestration tools (e.g., Airflow, ADF). Understanding of data warehousing , big data ecosystems , and data modeling concepts. Familiarity with CI/CD processes in a data engineering context. Nice to Have: Experience with real-time data processing using tools like Kafka or Kinesis. Familiarity with machine learning model deployment in data pipelines. Experience working in an Agile environment. Show more Show less

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