Senior Level Data Analytics Developer Jobs

Senior level data analytics developer jobs place experienced professionals at the center of analytics strategy, owning end-to-end data solutions and directing the teams that build and maintain them. Openings are concentrated across Technology & Software, Consulting & Professional Services, and Biotechnology & Pharmaceuticals, with 33% remote or hybrid availability, and employers like CVS Health, Revolution Medicines, and Infojini hiring at this level now.

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Overview

Open roles701+
Top stateTexas
Top employerCVS Health
Top cityAustin, TX
Work type67% On-site
Top industryTechnology

Showing 5 of 701+ Senior Level Data Analytics Developer jobs

Dotnet Developer
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New 31m ago
Dotnet Developer
KPG99 INC
Charlotte, North Carolina
Software Engineering
Cloud & DevOps
Full-stack Engineering
Backend Engineering
Hybrid
Bachelor's

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Senior Full Stack Developer
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New 1h ago
Senior Full Stack Developer
COGENT DATA SOLUTIONS LLC
Austin, Texas
Software Engineering
Cloud & DevOps
Full-stack Engineering
Backend Engineering
Hybrid
None

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HL7 developer
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New 3h ago
HL7 developer
Infojini Inc
Austin, Texas
Software Engineering
Data Engineering
On-Site
None

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Sr. Salesforce Developer
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New 4h ago
Sr. Salesforce Developer
Sligo Software Solutions Inc.
Albany, New York
Software Engineering
Technical Product & Program Management
Backend Engineering
$71.00 - $71.00/hr
On-Site
Bachelor's

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Senior Java Developer
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New 4h ago
Senior Java Developer
MAES Solutions
Texas
Software Engineering
Cloud & DevOps
Backend Engineering
On-Site
None

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Senior Level Data Analytics Developer Job Market

Who's Hiring

  • CVS Health13
  • Revolution Medicines12
  • Infojini11
  • Artech10
  • NVIDIA9

Top Industries Hiring

  • Technology & Software322
  • Consulting & Professional Services90
  • Biotechnology & Pharmaceuticals34
  • Insurance27
  • Banking & Financial Services22

Senior Level Data Analytics Developer Jobs: Frequently Asked Questions

How do I get a senior level data analytics developer job?

Employers hiring at the senior level look for candidates who have owned full analytics pipelines, not just contributed to them. Demonstrating that you have made architectural decisions, mentored junior developers, and translated complex data outputs into business outcomes gives you a clear edge. A portfolio of high-impact projects and evidence of cross-functional leadership strengthens your candidacy significantly.

Which companies hire senior level data analytics developers?

Companies hiring senior level data analytics developers right now include CVS Health, Revolution Medicines, and Infojini, based on current listings on Migrate Mate as of November 2026. Hiring at this level tends to come from large enterprises and growth-stage technology firms that run mature data organizations and need experienced developers to lead analytical initiatives.

Are there remote senior level data analytics developer jobs?

Yes, remote and hybrid options are well represented at the senior level. About 33% of senior level data analytics developer openings are remote or hybrid as of November 2026, reflecting the demand for experienced developers who can operate independently and collaborate across distributed teams without requiring on-site supervision.

What makes a data analytics developer role senior level?

Senior level roles are defined by scope and ownership rather than just technical proficiency. At this stage, you are expected to set the analytical direction for projects, make data modeling and architecture decisions, and ensure the quality of work produced by the broader team. Mentoring junior and mid-level developers and communicating findings directly to business stakeholders are core expectations, not optional responsibilities.

Which industries hire the most senior level data analytics developers?

Senior Level data analytics developer roles concentrate in Technology & Software, Consulting & Professional Services, and Biotechnology & Pharmaceuticals, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they manage large, complex data ecosystems where experienced developers who can govern data quality and deliver actionable analytics at scale are critical to operations.