Job Description
to-end design and optimization of Databricks ETL pipelines to ensure high-quality data delivery.
Develop scalable data ingestion and transformation workflows by leveraging the full power of the
Apache Spark framework.
Robust experience in Azure Synapse Analytics.
Manage complex data lifecycles involving both structured and unstructured datasets from diverse
originating sources.
Fine-tune Spark jobs to balance peak performance with cost-efficiency and long-term scalability.
Establish robust CI/CD patterns and version control standards for all Databricks-based workflows.
Collaborate with stakeholders across engineering, data science, and analytics to translate
business needs into technical solutions.
Enforce rigorous security protocols and access management policies within the Databricks
workplace.
Diagnose and resolve complex bottlenecks related to big data processing and system scalability.

Required Skills: - - - - - - -




Proven track record of developing high-performance solutions using Databricks and Apache Spark (proficient in PySpark, Scala, or Java). querying. (proficient in PySpark, Scala, or Java). querying. and warehousing solutions like ADLS, S3, or BigQuery. (proficient in PySpark, Scala, or Java). querying. and warehousing solutions like ADLS, S3, or BigQuery. Warehousing environments. (proficient in PySpark, Scala, or Java). querying. and warehousing solutions like ADLS, S3, or BigQuery. Warehousing environments. engineering. (proficient in PySpark, Scala, or Java). querying. and warehousing solutions like ADLS, S3, or BigQuery. Warehousing environments. engineering. performance tuning and optimization.
Expert-level command of SQL for complex data modeling, transformation, and analytical querying.
Deep familiarity with cloud ecosystems (Azure, AWS, or GCP), with specific expertise in storage
Significant experience building end-to-end ETL/ELT pipelines and managing scalable Data
Solid grip on CI/CD pi

📌 Data Engineer Telangana
🏢 HuntingCube
📍 Telangana