DataBricks - Lead Programmer Analyst
Bilvantis Technologies
- Location
- Hyderabad, Telangana, India
- Job type
- Full-time
Required skills
- Python
- Agile
- Airflow
- AWS
- Apache
- Apache Spark
- Azure
- caching
- cloud data services
- communication skills
- Confluence
- cross-functional
- data modeling
- data warehouse
- Databricks
- design patterns
- DevOps
- ETL
- GCP
- Git
- infrastructure-as-code
- Jira
- Kafka
- machine learning
- Spark
- SQL
- Terraform
- version control
- Unity
About the role
Bilvantis Technologies
Website:
bilvantis.io
Job details:
Job Description: DataBricks - Lead Programmer Analyst
We are looking for a highly self-motivated individual with DataBricks development as a Lead Programmer Analyst:
Required Skills & Qualifications
- Experience should have 5 to 7 Years of Data Engineering.
- Expert-level Apache Spark skills using PySpark (Scala a plus).
- Strong proficiency in SQL for data transformation and performance tuning.
- Solid experience with Delta Lake and the Lakehouse/medallion architecture.
- Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its data services.
- Experience with workflow orchestration (Databricks Workflows, Delta Live Tables, or Airflow).
- Strong understanding of data modeling, data warehousing, and ETL/ELT design patterns.
- Experience with Python for data engineering and automation.
- Familiarity with CI/CD, Git, and DevOps practices for data.
- Good understanding of data governance, security, and Unity Catalog.
- Strong problem-solving and communication skills.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Good To Have
- Databricks Certified Data Engineer Associate or Professional certification.
- Experience with streaming technologies (Structured Streaming, Kafka, Event Hubs, Pub/Sub).
- Exposure to machine learning workflows and MLflow.
- Experience with Infrastructure-as-Code (Terraform) and cloud cost optimization.
- Experience working in Agile delivery environments.
- Experience in data warehouse design and maintenance
- Experience in agile development processes using Jira and Confluence.
- Experience in cross-functional teams.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines on the Databricks Lakehouse Platform.
- Build and optimize Apache Spark (PySpark/Scala) jobs for batch and streaming data processing.
- Implement and manage Delta Lake tables, including partitioning, schema evolution, and performance tuning (Z-ordering, caching, file compaction).
- Develop and orchestrate workflows using Databricks Workflows, Delta Live Tables (DLT), and job scheduling tools such as Airflow.
- Implement the medallion architecture (bronze, silver, gold layers) for reliable, governed data.
- Integrate Databricks with cloud data services (AWS, Azure, or GCP) and source systems.
- Apply data governance and security using Unity Catalog, access controls, and lineage.
- Optimize cluster configuration, cost, and performance across workloads.
- Collaborate with data analysts, data scientists, and business stakeholders to deliver trusted datasets.
- Ensure data quality, testing, monitoring, and observability across pipelines.
- Contribute to CI/CD practices for data engineering (version control, automated deployment).
Click on Apply to know more.
This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.
