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Databricks Data Engineer
2 weeks ago
Job Title: Databricks Data Engineer
Experience Level: 5 to 7 Years
Location: Ahmedabad
Employment Type: Full-Time
Certifications Required:
- Databricks Certified Data Engineer Associate
- Databricks Certified Data Engineer Professional
- Cloud Certifications (Preferred): Azure, AWS, GCP
Job Summary:
We are seeking a highly skilled and certified Databricks Data Engineer to join our dynamic data engineering team. The ideal candidate will have hands-on experience in implementing Lakehouse architectures, upgrading to Unity Catalog, and building robust data ingestion pipelines. This role demands proficiency in Python, PySpark, SQL, and Scala, along with a strong understanding of big data technologies, streaming workflows, and multi-cloud environments.
Key Responsibilities:
Lakehouse Implementation:
- Design and implement scalable Lakehouse architecture using Databricks.
- Optimize data storage and retrieval strategies for performance and cost-efficiency.
Unity Catalog Upgrade:
- Lead and execute Unity Catalog upgrades across Databricks workspaces.
- Ensure secure and compliant data governance and access control.
Data Ingestion & Migration:
- Develop and maintain data ingestion pipelines from various sources (structured, semi-structured, unstructured).
- Perform large-scale data migrations across cloud platforms and environments.
Pipeline Development:
- Build and manage ETL/ELT pipelines using PySpark and SQL.
- Ensure data quality, reliability, and performance across workflows.
Big Data Streaming & Workflows:
- Implement real-time data streaming solutions using Spark Structured Streaming or similar technologies.
- Design workflow orchestration using tools like Airflow, Databricks Workflows, or equivalent.
Multi-Cloud Expertise (Preferred):
- Work across Azure, AWS, and GCP environments.
- Understand cloud-native services and integration patterns for data engineering.
Collaboration & Documentation:
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
- Document technical designs, data flows, and operational procedures.
Required Skills & Qualifications:
- 57 years of hands-on experience in data engineering roles.
- Strong expertise in Databricks platform and ecosystem.
- Proficiency in Python, PySpark, SQL, and Scala.
- Experience with Lakehouse architecture and Unity Catalog.
- Proven track record in building scalable data ingestion pipelines and performing data migrations.
- Familiarity with big data technologies such as Delta Lake, Apache Spark, Kafka, etc.
- Understanding of data lake concepts and best practices.
- Experience with streaming data and workflow orchestration.
- Certified as Databricks Data Engineer Associate and Professional (mandatory).
- Cloud certifications in Azure, AWS, or GCP are a strong plus.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration abilities.
Nice to Have:
- Experience with CI/CD pipelines and DevOps practices in data engineering.
- Exposure to data cataloging tools and metadata management.
- Knowledge of data security, privacy, and compliance standards.
