Lead Data Engineer [AQ-11617]
@ Aquent TalentLead Data Engineer [AQ-11617]
About the job
A global leader in athletic gear, focusing on innovation and sustainability. The role involves building data solutions, supporting analytics, and collaborating with cross-functional teams in a fast-paced environment.
Requirements
- 8-10+ years in data engineering
- Strong Python or Scala skills
- Experience with Spark and SQL
- Hands-on with Databricks or Snowflake
- Support AI/ML initiatives
Qualifications
- Experience in global consumer/retail
- Big data environment expertise
- Excellent communication skills
- Agile/Scrum experience
- Cloud platform knowledge
Full job description
Data Engineer IV (Senior / Lead Level)
Location: Portland, OR (Hybrid – 4 days onsite, 1 remote)
Type: Contract (with potential extension)
Start: ASAP (urgent need)
About the Role
We’re seeking a highly experienced Data Engineer to join a fast-paced, collaborative team focused on building scalable data products and improving business performance. This role sits at the intersection of data engineering, analytics, and product development, supporting critical initiatives that drive profitability and operational efficiency.
You’ll work closely with product managers, analysts, and engineering teams to design and deliver modern data solutions at scale.
What You’ll Do
- Design, build, and maintain scalable data pipelines (batch and streaming)
- Develop and optimize data products and datasets for business and analytics use
- Translate product requirements and backlog items into technical solutions
- Contribute to data architecture, frameworks, and best practices
- Build reusable data utilities, libraries, and frameworks
- Partner cross-functionally with product, analytics, and business stakeholders
- Ensure data quality, reliability, and performance through testing and monitoring
- Troubleshoot issues and perform root cause analysis
- Support and evolve CI/CD pipelines and automation workflows
- Contribute to AI/ML data initiatives and enable downstream use cases
Must-Have Qualifications
- Prior experience working within a large global consumer or retail organization (environment familiarity required)
- 8–10+ years of experience in data engineering or big data environments
- Strong programming skills in Python (or Scala)
- Deep experience with distributed data processing (e.g., Spark)
- Advanced SQL and data warehousing expertise
- Hands-on experience with modern data platforms such as Databricks, Snowflake, or equivalents
- Proven ability to build and scale end-to-end data pipelines
- Experience supporting or enabling AI/ML or advanced analytics initiatives
- Strong communication skills and ability to work across technical and non-technical teams
- Experience working in Agile/Scrum environments
Preferred Qualifications
- Experience in finance, profitability, or margin-focused analytics
- Experience with cloud platforms (AWS or equivalent)
- Familiarity with workflow orchestration tools (e.g., Airflow or similar)
- Experience with streaming technologies (e.g., Kafka, Kinesis, or equivalents)
- Exposure to CI/CD, infrastructure as code, and automation tools
- Experience supporting BI/reporting tools and analytics workflows
- Knowledge of NoSQL databases
- Relevant certifications (cloud or data platforms)
What Success Looks Like
- Delivering high-quality, scalable data solutions that support business decisions
- Improving data accessibility, performance, and reliability
- Enabling teams with better tools, cleaner data, and faster insights
- Driving efficiency and reducing friction across data workflows
#LI-BC1
Client Description
Global leader in athletic footwear, apparel, and equipment. Our client focuses on innovation, performance, and marketing, partnering with top athletes and teams. The company emphasizes sustainability and digital advancements to enhance the sports experience.
#LI-Onsite
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