Role & responsibilities

- Develop, and deploy end-to-end data pipelines and solutions on Databricks, integrating with various data sources and systems.
- Collaborate with cross-functional teams to understand data, and deliver effective BI solutions.
- Implement data ingestion, transformation, and processing workflows using Spark (PySpark/Scala), SQL, and Databricks notebooks.
- Develop and maintain data models, ETL/ELT processes ensuring high performance, reliability, scalability and data quality.
- Build and maintain APIs and data services to support analytics, reporting, and application integration.
- Ensure data quality, integrity, and security across all stages of the data lifecycle.
- Monitor, troubleshoot, and optimize pipeline performance in a cloud-based environment.
- Integrate data from various sources, including APIs, relational and non-relational databases, IoT devices, and external data providers.
- Ensure adherence to data governance, security, and compliance policies.

Required Skills and Experience

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 7+ years of hands-on experience in data engineering, with a strong focus on Databricks and Apache Spark.
- Strong programming skills in Python/PySpark and/or Scala, with a deep understanding of Apache Spark.
- Experience with Azure Databricks.
- Solid SQL skills for data manipulation, analysis,



and performance tuning.
- Strong understanding of data structures and algorithms, with the ability to apply them to optimize code and implement efficient solutions.
- Solid understanding of data architecture, data modeling, ETL/ELT processes, and data warehousing concepts.
- Experience building and maintaining ETL/ELT pipelines in production environments.
- Familiarity with Delta Lake, Unity Catalog, or similar technologies.
- Experience working with structured and unstructured data, including JSON, Parquet, Avro, and time-series data.
- Familiarity with CI/CD pipelines and tools like Azure DevOps, version control (Git), and DevOps practices for data engineering.
- Excellent problem-solving skills, attention to detail, and ability to work independently or as part of a team.
- Strong communication skills to interact with technical and non-technical stakeholders.

Preferred Qualifications

- Experience with Delta Lake and Databricks Workflows.
- Exposure to real-time data processing and streaming technologies (Kafka, Spark Streaming).
- Exposure to data visualization tool Databricks Genie for data analysis and reporting.
- Knowledge of data governance, security, and compliance best practices.
- Must Have Skills: Spark, Migration Experience, ETL

Work Mode : 5days office a week

📌 Senior Data Engineer (Hyderabad)
🏢 Koantek
📍 Hyderabad