Position Overview
We are seeking a highly skilled and experienced Databricks Developer / Data Engineer to join our team. The ideal candidate will have a minimum of 5 years of hands-on experience working with Databricks on leading cloud platforms such as AWS and Azure. You will be responsible for designing, building, and optimizing scalable data pipelines, collaborating with cross-functional teams, and driving data-driven decision making across the organization.
Key Responsibilities
Design, develop, and maintain scalable data pipelines and ETL processes using Databricks on AWS and Azure.
Optimize Spark jobs for performance, reliability, and cost-efficiency.
Integrate Databricks workflows with cloud-native storage solutions (S3, ADLS).
Implement data quality, validation, and governance best practices.
Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions.
Troubleshoot and resolve issues in production data pipelines.
Document technical solutions and create knowledge-sharing materials for the team.
Must Have Skills
Databricks Platform Expertise: 5+ years of hands-on experience developing solutions on Databricks, including workspace management, notebook development, job scheduling, and cluster configuration.
Cloud Platform Experience: Proven experience in deploying and managing Databricks environments on AWS and Azure.
Apache Spark: Advanced knowledge of Spark (PySpark/Scala/SQL) for data processing and analytics.
ETL \& Data Pipeline Development: Expertise in building robust ETL processes and data pipelines.
Programming Languages: Proficiency in Python and/or Scala.
Cloud Storage Integration: Experience integrating with S3, ADLS, or similar cloud storage services.
SQL Skills: Strong ability to write and optimize complex SQL queries.
Data Modeling: Solid understanding of data modeling concepts and best practices.
Version Control: Familiarity with Git or similar version control systems.
Problem Solving: Excellent troubleshooting and analytical skills.
Good to Have Skills
Experience with CI/CD pipelines and DevOps practices for data engineering.
Knowledge of Delta Lake and advanced Databricks features (e.g., MLflow, Databricks SQL).
Experience with other cloud platforms (Google Cloud Platform, etc.).
Exposure to data visualization tools (Power BI, Tableau, etc.).
Understanding of data security, compliance, and privacy standards.
Hands-on experience with streaming data (Kafka, Spark Streaming).
Familiarity with REST APIs and data integration patterns.
Ability to mentor junior team members and conduct code reviews.
Experience with infrastructure as code (Terraform, CloudFormation).
Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Minimum 5 years of experience in Databricks development on AWS and/or Azure.
Strong communication skills and ability to work in a collaborative environment.
Relevant certifications (Databricks, AWS, Azure) are a plus.