Posted:1 day ago|
Platform:
On-site
Full Time
In this role, the Databricks Developer is responsible for solving the real world cutting edge problem to meet both functional and non-functional requirements.
Design and develop scalable data pipelines using Databricks (PySpark/SQL/Delta Live Tables).
Implement ETL/ELT frameworks leveraging the Lakehouse (Bronze, Silver, Gold) architecture.
Implement and manage data governance using Unity Catalog to ensure secure access, compliance, and centralized management of data, users, and permissions across the Databricks Lakehouse.
Optimize data models, queries, and workflows for scalability, cost, and performance.
Act as Databricks SME and provide guidance on best practices, governance, and security.
Mentor junior developers, review code, and enforce coding standards.
Integrate Databricks with cloud storage, APIs, warehouses, and BI tools.
Implement orchestration using ADF, Airflow, Step Functions, or Databricks Workflows.
Build reusable accelerators and frameworks for ingestion, transformation, and monitoring.
Enable data quality, validation, and reconciliation (using tools like Great Expectations or custom).
Set up monitoring, logging, and alerting dashboards for pipeline health.
Collaborate with business stakeholders, architects, and analysts to deliver solutions.
Support migration of legacy pipelines into Databricks Lakehouse.
Contribute to architectural decisions, POCs, and innovation initiatives.
Bachelor's degree (CS, CE, CIS, IS, MIS, Engineering) or equivalent work experience.
Experience in data engineering with at least Databricks experience.
End-to-end implementation of at least 2 Databricks projects(migration/integration).
Strong background in batch and streaming data pipelines.
Proficiency in Python (preferred) or Scala for Spark-based development.
Expertise in SQL & Spark-SQL, data structures, and algorithms.
Deep knowledge of Databricks components: Delta Lake, DLT, dbConnect, REST API 2.0, Workflows orchestration.
Strong in performance optimization for pipelines (efficiency, scalability, cost reduction).
Hands-on experience with Apache Spark, Hive, and Lakehouse architecture.
Cloud expertise (Azure/AWS) includes storage (ADLS/S3), messaging (ASB/SQS), compute (ADF/Lambda), and databases (CosmosDB/DynamoDB/Cloud SQL).
Experience writing unit tests and integration tests for data pipelines.
Ability to work with architects and lead engineers to design solutions meeting functional & non-functional requirements.
Team player with experience in teams of 5+ engineers.
Strong communication and client-facing skills.
Keeps updated with emerging technologies and industry trends.
Strong analytical and problem-solving abilities.
Positive attitude towards continuous learning and upskilling
Good to have Databricks SQL Endpoint understanding.
Good to have understanding on LakeflowConnect, Lakeflow Declarative Pipelines
Good To have CI/CD experience to build the pipeline for Databricks jobs.
Good to have if worked on migration project to build Unified data platform.
Good to have knowledge of DBT.
Good to have knowledge of docker and Kubernetes.
Certification on Databricks Associate level.
Any one Cloud Certification (AWS/Azure) Practitioner or Associate Level
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