Data Engineer

Job Category:
Data
Job Type:
Hybrid
Job Location:
Seattle Washington
Compensation:
Depends on Experience
W2:
W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.
Job Description
US Work Authorization Requirement:
Candidates must be legally authorized to work in the United States without employer sponsorship. This includes, but is not limited to, U.S. Citizens, Permanent Residents, and other individuals with valid U.S. work authorization.
**Job Description:**
We are seeking a
Senior Data Engineer
to join a highly collaborative,
onsite data engineering team
supporting
large-scale cloud migration and data platform modernization initiatives
. This is a
hands-on, end-to-end role
requiring deep expertise in
Databricks, PySpark, SQL, and AWS-based ETL pipelines
.
The ideal candidate is a senior practitioner who can not only build and deliver solutions independently but also
evaluate existing architectures, identify gaps, and propose modern, scalable approaches
aligned with Databricks and cloud data engineering best practices. You will work in an
Agile environment
, partnering closely with engineering peers, architects, and business stakeholders.
**Key Responsibilities**

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and Apache Spark (PySpark)
• Lead and support migration of data pipelines and applications from on-premises environments to AWS
• Build robust data ingestion frameworks for structured, semi-structured, and unstructured data sources
• Write, optimize, and maintain complex SQL queries across RDBMS, data lakes, and federated data environments
• Review existing data solutions and recommend architectural improvements for performance, scalability, and maintainability
• Develop reusable frameworks and components to standardize data processing patterns
• Tune and optimize Spark jobs for performance and cost efficiency in cloud environments
• Build, deploy, and support solutions end-to-end, from development through production
• Implement CI/CD pipelines and follow version control best practices
• Enforce data quality, validation, security, and governance standards
• Collaborate with data architects, analysts, and business stakeholders to translate requirements into technical solutions
• Participate in Agile ceremonies, including sprint planning, estimation, and retrospectives
• Troubleshoot, debug, and resolve production pipeline issues
• Take full ownership of solutions from design through production support

**Required Qualifications**

• 12+ years of overall IT experience with strong focus on data engineering
• Hands-on expertise with Databricks SaaS, Python, and PySpark
• Ability to independently design and build ETL pipelines
• Expert-level SQL skills, including writing and optimizing complex queries
• Strong experience with AWS-based ETL services, including:
• AWS Glue
• EC2
• EMR
• Amazon S3
• Solid understanding of Data Lake and Lakehouse architectures
• Experience working with RDBMS and large-scale analytical datasets
• Proven experience deploying production code using Git and CI/CD pipelines
• Comfortable working onsite full-time in a collaborative team environment
• Strong communication skills with a solution-oriented mindset
• Ability to own solutions end to end, from architecture through operations

Education
Bachelor’s degree in
Computer Science
or equivalent professional experience
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