AWS Data Engineer (Databricks & DBT)
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Job Description
Hi,
Hope you are doing great!!!!!
We have a very good position with our client, please let me know if you are comfortable with the job description below with your updated resume.
Position AWS Data Engineer (Databricks & DBT)
Location : Lebanon, NJ (Hybrid)
Duration: : 12+Month
Interview: Phone/Video
Job Description
We are seeking a skilled AWS Data Engineer with strong expertise in Databricks and DBT to design, build, and optimize scalable data pipelines and analytics solutions. The ideal candidate will have hands-on experience with modern data architectures, ETL/ELT processes, and cloud-based data platforms.
Key Responsibilities
1. Data Pipeline Design & Development
- Design, build, and optimize robust ETL/ELT pipelines using AWS services such as S3, Glue, and Lambda.
- Leverage the Databricks platform (Spark, Delta Lake, DLT) for scalable data processing.
- Ingest and process large volumes of structured and semi-structured data from multiple sources, including APIs, databases, and streaming platforms (Kafka/Kinesis).
- Build and maintain centralized data lake/lakehouse architectures.
2. Data Transformation & Modeling
- Develop and maintain data models such as star schema, snowflake schema, and medallion architecture using DBT (Data Build Tool).
- Write efficient and complex SQL queries and Python/PySpark code for data transformation and validation.
- Implement data quality checks, testing, and documentation within DBT workflows.
- Ensure adherence to data governance and security standards.
3. Orchestration & Automation
- Orchestrate and monitor workflows using Databricks Jobs and tools like AWS MWAA (Apache Airflow).
- Implement CI/CD pipelines and manage version control using Git.
- Automate deployment of data engineering artifacts including code, configurations, and DBT models.
4. Performance Optimization & Operations
- Monitor, troubleshoot, and resolve issues in production pipelines to ensure high performance and reliability.
- Optimize Spark jobs and leverage Delta Lake features such as partitioning and Z-Ordering.
- Ensure cost optimization and scalability of data solutions.
5. Collaboration & Stakeholder Engagement
- Collaborate with data scientists, analysts, and business stakeholders to gather requirements and deliver insights.
- Provide guidance on data best practices, governance, and quality standards.
- Work in an Agile environment using tools like JIRA.
Required Skills
- Strong proficiency in SQL
- Hands-on experience with DBT Core and DBT Cloud
- Experience with AWS services, especially Redshift, S3, Glue, Lambda
- Strong experience with Databricks on AWS
- Experience working with SQL Server
- Familiarity with CI/CD pipelines and Git
- Experience with Stonebranch (or similar scheduling tools)
- Experience working in an Agile environment (JIRA)
Thanks
Ankit Singh
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