Overview
On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
Skills
SQL
ETL
ALTERYX
Job Details
Onsite position - Denver, Colorado
S OR GREENS CARDS
No Sponsorship
No Corp to Corp
MUST HAVE 12+ YEARS OF EXPERIENCE
Data Engineering Manager Requirements:
- Professional experience in data engineering, data analytics, or related roles.
- Deep expertise in SQL, including complex stored procedures.
- Strong experience with ETL processes designing, building, and maintaining pipelines to clean and aggregate data.
- Hands-on experience building and supporting Alteryx workflows.
- Familiarity with Amazon Redshift or other cloud data warehouses.
- Ability to thrive in an agile, fast-paced, and dynamic environment, adapting priorities quickly (2 3 day turnaround on projects).
- Excellent communication skills, comfortable interfacing with both technical teams and business leaders.
- Strong problem-solving and analytical mindset comfortable working with complex data and numbers.
Nice to Have Skills:
- 2 years of experience managing a team of developers or analysts.
- Prior experience coaching teams through process improvement, education, and solution development.
- Experience with compensation, incentives, or payroll data.
- Telecom industries experience.
- Data Engineering Manager Responsibilities:
- Lead and manage a team of developers and analysts responsible for designing, building, and maintaining data workflows and pipelines.
- Develop, maintain, and optimize SQL stored procedures, ETL processes, and data aggregation pipelines.
- Oversee and expand Alteryx workflows to automate daily reporting and data processing; monitor and troubleshoot issues proactively.
- Support Amazon Redshift and other data warehouse environments, ensuring scalable and reliable data architecture.
- Convert complex business requirements (incentive/compensation rules) into executable logic and code for reporting and payment generation.
- Communicate regularly with business stakeholders and leadership to understand requirements, share progress, and educate teams on data solutions.
- Deliver projects end to end: requirements gathering, development, testing, deployment, and post-launch support.
- Maintain a proactive approach to issue identification, resolution, and escalation when needed.
- Coach and mentor team members, providing guidance on best practices and professional development.
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