About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT Services and IT Consulting.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

Confidential Client is building an AI-first product that extracts metadata from legacy ETL tools, databases, and vendor formats to produce trusted lineage and dependency maps. As a Staff Software Engineer (Data Integration), you will own connectors and parsers that make the product work and help shape the connector framework.

• Build and maintain connectors for legacy ETL platforms, databases, and modern cloud data systems.
• Parse XML, SQL, repository exports, scripts, and vendor-specific formats into structured metadata.
• Convert extracted metadata into accurate data lineage and dependency models.
• Create automated tests and known-good datasets to verify connector correctness and prevent regressions.
• Improve the connector framework, document reusable patterns, and collaborate with the Principal Architect on design decisions.
• Integrate AI into your daily workflow to accelerate reverse-engineering, coding, testing, debugging, and documentation while owning final technical correctness.

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What We’re Looking For

• Strong experience in data engineering, metadata systems, or systems integration.
• Practical, hands-on work with ETL platforms, SQL parsing, data lineage, or transformation logic.
• Proven ability to reverse-engineer unfamiliar or poorly documented systems.
• Comfortable developing in TypeScript and building robust automated tests.
• Demonstrated experience using AI tools as an integrated part of the development process (not just occasional use).
• Bias for shipping quickly, testing thoroughly, and fixing defects proactively.

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Nice to Have

• Experience with Informatica PowerCenter, IBM DataStage, Talend, SSIS, or similar ETL platforms.
• Familiarity with graph models, OpenMetadata, OpenLineage, compilers, or parser construction.
• Experience delivering software into regulated or security-reviewed environments.

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Compensation, Work Location & Eligibility

• Estimated Compensation Range: $180,000—$225,000 USD (base pay). Final offer will consider experience, skills, and internal equity. Additional discretionary bonuses and benefits may apply.
• Employment type: Full-time (telecommute-friendly).
• This role is open to candidates who are authorized to work for any U.S. employer without sponsorship. Confidential Client is not able to sponsor or transfer an employment visa at this time.
• To be considered, candidates must currently reside in one of the following U.S. states or DC: AL, AR, AZ, CA, CO, CT, DE, FL, GA, IA, ID, IL, IN, KS, MA, MD, MI, MN, MO, NC, NH, NJ, NV, NY, OH, OK, OR, PA, TN, TX, VA, WI, or Washington, DC.

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Why Join

You’ll join a small, early-stage, funded product team focused on practical, high-impact work. Expect close collaboration with experienced leaders, a chance to influence product direction, and opportunities to help deliver solutions that matter to regulated enterprises.

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Minimum Education

• Bachelor’s degree or equivalent practical experience in Computer Science, Engineering, or a related field (per source posting).

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Technology & Keywords

Key technologies and focus areas for this role: TypeScript, ETL connectors, SQL parsing, metadata extraction, data lineage, automated testing, AI-assisted development, reverse engineering, cloud data systems.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.