Is Data, Analytics & AI a Good Job Market in San Antonio-New Braunfels, TX?

Executive Verdict

Market rating: competitive | Confidence: High

This is a competitive market, not a dead one. San Antonio-New Braunfels unemployment was 4.8% in June 2026, up from 4.1% in May, while the metro still added 4,800 jobs over the year and total nonfarm employment was up 0.6052% year over year.[16][31][17] For this occupation family, Texas signals are mixed: Revelio Public Labor Statistics shows Data, Analytics & AI employment down 0.8% year over year even as active postings rose 28.5% in July 2026.[9][10] That usually means openings exist, but employers are choosier and lean toward candidates who can contribute quickly with Python, SQL, BI, or ML-adjacent skills.[3]

Best positioned: The best odds right now belong to candidates with Python, SQL, Tableau or Power BI, and a clear business domain story for finance, government, healthcare, or enterprise operations work.[4][3]

Main caution: Do not treat this as a remote-first generalist market: about 65% of local postings are on-site, the largest share is mid-career, and the typical active posting has been open around 44 days.[5][1][11]

What Changed Recently

• The local labor backdrop softened between May and June: metro unemployment moved from 4.1% to 4.8%.[31][16]: That does not mean data hiring disappeared, but it usually raises the bar on interviews and slows offer timing.
• Business-facing employers look healthier than pure info-sector employers. Professional and Business Services employment in the metro was up 3.5761% year over year in June 2026, while Information employment was down 7.0652%.[19][18]: For job seekers, that tilts the best odds toward analytics inside finance, consulting, government, and healthcare rather than betting only on traditional tech-media employers.
• Texas occupation data got more two-sided in July 2026: Data, Analytics & AI employment was down 0.8% year over year, but active postings were up 28.5%.[9][10]: That is a selective-hiring pattern: more advertised demand, but not necessarily easy hiring for broad generalists.
• National hiring stayed cautious. Total U.S. nonfarm payrolls were up just 0.1993% year over year in July 2026, and the national job openings rate was 4.4% in June 2026.[24][35]: In San Antonio, that supports a lower-churn market where employers keep roles open longer and expect closer skill matches.
• AI expectations moved further into analyst work: machine learning mentions in data-analyst postings doubled from 7% to 14% nationally in 2026.[6]: Even analyst candidates now benefit from showing some modeling, automation, or AI-assisted analysis instead of only dashboarding.

What This Means for You

Entry-Level Candidates

Difficulty: Harder than average locally because only about 25% of sampled postings are entry-level, most roles still ask for a bachelor's degree, and employers want Python, SQL, and dashboard tools rather than spreadsheet-only backgrounds.[1][2][3]

Best target: Aim for on-site or hybrid analyst paths in finance, healthcare, and public-sector organizations where business context matters as much as advanced modeling.[4][5]

Biggest mistake: Applying as a generic 'data enthusiast' without a portfolio that proves SQL, Python, one BI tool, and a business recommendation.

Next step: Build two tight projects in the next month: one SQL plus dashboard project and one Python analysis that shows basic forecasting, classification, or workflow automation.[3][6][7]

Mid-Career Candidates

Difficulty: Manageable if you already own business outcomes; harder if your background is only ad hoc reporting. The local sample skews mid-career at about 40%, and the better-paid local ranges cluster in more technical or decision-oriented work.[1][8]

Best target: Target enterprise analytics teams in financial services, consulting, government, and healthcare, especially roles that combine Python or SQL with stakeholder-facing decision support.[4][3]

Biggest mistake: Leading with tool lists instead of showing how you improved forecasting, reduced cycle time, or changed an operating decision.

Next step: Rewrite your resume around three quantified outcome stories and one modern-stack story: Python, SQL, Tableau or Power BI, plus some ML or cloud exposure.[3][6]

Career Switchers

Difficulty: Possible, but you will be screened hard on proof of execution because the market is selective and most roles are not built as apprenticeships.[9][10][11]

Best target: Use adjacent, domain-heavy paths first, such as finance, operations, healthcare, or compliance analytics, where prior industry knowledge can offset a thinner technical resume.[4]

Biggest mistake: Trying to jump straight into AI branding before proving analysis, experimentation, and business communication.

Next step: Pick one domain, one BI tool, and one coding language, then build a portfolio around that combination instead of scattering effort across too many certificates.[12][3]

Salary Reality

high pay highly concentrated

The cleanest local wage anchor is a federal local series for statisticians: median annual pay is $97,990, with $75,200 at the 25th percentile and $128,830 at the 75th percentile in San Antonio-New Braunfels.[13] Fresher posting data shows listed salary ranges centered on about $105k to $154k, while local salary aggregators put data analyst pay anywhere from a $76,549 average to a $112,116 average depending on method, and USAA-specific data analyst median total compensation at $80K.[8][14][22][23]

This is a market where real six-figure analytics pay exists, and San Antonio's cost-of-living index is around 91, roughly 9% below the national average.[36] That means a good analytics offer can stretch better here than in larger high-cost metros, but the best pay is not spread evenly across all titles.[36][8]

The tradeoff is selectivity. About 65% of local roles are on-site, about 40% of the sample is mid-career, and active postings stay open around 44 days, which suggests employers can wait for closer matches instead of hiring fast.[5][1][11]

Best-paying path: The strongest pay tends to sit in data science and ML-heavier tracks: local data scientist median pay is cited at $103,290, Texas new-opening offered salary for the broader occupation family was about $123,548, and one 2026 comparison says data scientists earn about 25% more than data analysts nationally on median base pay.[15][27][37]

Caution: Do not overread the top-end figures. They mix lagged government wage data, posted salary bands, and salary-aggregator estimates from different dates and methods, so they are better used as negotiation guardrails than as a guaranteed market price.[8][13][14][23][15]

Where the Opportunities Are Concentrated

Real opportunities are spread across a long tail rather than dominated by one giant local employer. Over the last 90 days, the local sample showed more than 50 postings across more than 30 companies, and hiring was fragmented across employers.[20][30] The most active named employers in the sample included SWBC Mortgage Corporation, IntelliGenesis LLC, YO IT Consulting, The Podmilsak Group, Deloitte, CACI, and Matricstek Inc, each with around 5 postings.[21] The best concentration is in business-facing environments. Within local postings, financial services and technology, information and internet each accounted for about 20% of activity, followed by software development at about 15%, then government and public sector and healthcare at about 10% each.[4] Paired with a 3.5761% year-over-year gain in San Antonio Professional and Business Services employment, that makes enterprise analytics a stronger local bet than waiting for a pure consumer-tech surge.[19][4] There is also a smaller satellite pocket in New Braunfels, where HiringCafe listed four operational data scientist jobs across four companies.[28] But because about 65% of local roles are on-site and only about 20% are remote, being geographically flexible inside the metro still matters.[5]

• Enterprise analytics in finance and services (high): This is the clearest local lane. Financial services is about 20% of local posting activity, and named employers include SWBC Mortgage Corporation alongside consulting and enterprise-service players.[4][21]
• Government and contractor analytics (moderate): Public-sector activity is about 10% of the local mix, some named employers include CACI and IntelliGenesis LLC, and a small share of postings ask for DoD 8140.01 or equivalent compliance signals.[4][21][12]
• Healthcare and operational data science (moderate): Healthcare is about 10% of the local mix, and there is a visible operational data science pocket in New Braunfels rather than only downtown San Antonio.[4][28]

Where to focus: If you want the best odds, focus first on enterprise analytics roles that mix Python or SQL with BI and stakeholder-facing business work inside finance, consulting, healthcare, and public-sector organizations.[4][3]

Skills and Credentials Worth Pursuing

• Python (table stakes): Python is the clearest local table-stakes skill, appearing in about 60% of sampled postings and spanning analyst through more technical roles.[3]
• SQL (table stakes): SQL shows up in about 40% of local postings, making it the minimum proof that you can work with production-style data rather than just spreadsheets.[3]
• Tableau or Power BI (differentiator): Tableau appears in about 30% of local postings and Power BI in about 20%, so one strong dashboard stack still improves hit rate in San Antonio.[3]
• Machine learning, PyTorch, and scikit-learn (premium): Machine learning, PyTorch, and scikit-learn each appear in about 20% of the local sample, and national analyst-posting mentions of machine learning doubled from 7% to 14% in 2026.[3][6]
• Google Cloud Certified - Associate Cloud Engineer (differentiator): It is one of the few certifications that shows up explicitly in local postings, and cloud capability is increasingly tied to modern analytics and ML delivery.[12][6]
• DoD 8140.01 / Security+ or equivalent (differentiator): A small but visible share of local postings asks for this requirement, which signals that some analytics roles sit near defense or regulated contractor environments.[12]
• AI literacy, prompt engineering, and workflow automation (differentiator): Employer surveys in 2026 point to AI literacy, prompt engineering, AI-powered data analysis, workflow automation, and ethical AI judgment as sought-after skills, while AI use has already spread to 88% of organizations and generative AI to 72%.[7][29]

Adjacent Roles to Consider

• FP&A analyst / financial analyst (bridge): Financial services accounts for about 20% of local posting activity, and employers in that lane already value structured analysis and business storytelling.[4]
• Healthcare operations analyst (bridge): Healthcare represents about 10% of the local mix, so domain-heavy operations roles can be a practical way into analytics work in this metro.[4]
• Compliance or risk analyst (pivot): Government and public-sector demand is about 10% of the local mix, some local employers are contractor-oriented, and a small share of roles ask for DoD 8140.01 or equivalent.[4][21][12]
• Product operations analyst (both): Newer AI-era roles increasingly sit closer to decision intelligence and data product work, which creates an opening for candidates who can translate analysis into workflow changes.[34][7]

30 / 60 / 90-Day Plan

First 30 Days

• Pick one lane now: enterprise analytics, government or contractor analytics, or healthcare operations analytics, because local demand is spread across those pockets rather than one unified tech scene.[4][21]
• Move Python, SQL, Tableau or Power BI, and one quantified business outcome into the top third of your resume.[3]
• Filter hard on work arrangement; about 65% of local roles are on-site and only about 20% are remote.[5]
• If you need sponsorship, check it before spending time on long applications; among postings that state a policy, about 0% mention visa sponsorship.[26]

Days 31-60

• Build one portfolio case tied to finance or operations and one tied to ML-assisted analysis or forecasting.[4][6]
• Add one signal that matches your lane: Google Cloud ACE for cloud-heavy analytics or DoD 8140.01/Security+ equivalency for contractor-adjacent roles.[12]
• Apply in employer clusters instead of one-offs: start with SWBC Mortgage Corporation, IntelliGenesis LLC, YO IT Consulting, Deloitte, CACI, and similar organizations.[21]
• Follow up on older openings instead of ignoring them; the typical active local posting has been open around 44 days.[11]

Days 61-90

• If interviews stall, widen your title mix toward FP&A analyst, risk analyst, healthcare operations analyst, or product operations analyst while keeping your analytics portfolio front and center.
• If your background is dashboard-heavy, add one shipped Python plus SQL project with a simple model or automated workflow before continuing broad applications.[3][6][7]
• If your pay target is above ordinary analyst levels, bias toward data science or ML-heavier openings and employers paying nearer the upper posted local bands or Texas offered-salary benchmarks.[8][27][15]
• Expand to nearby pockets such as New Braunfels when feasible; even niche operational data science demand is present there.[28]

Methodology and Confidence

This July 2026 report was generated on August 10, 2026. Latest direct national data: August 2026. Latest direct San Antonio-New Braunfels, TX data: August 2026.

Confidence: Overall confidence: High. Recent local labor-market data is supported by current employer, salary, and skill signals.

Limitations

• Local wage data is not available here for every title inside Data, Analytics & AI, so the report uses a local statistician wage series as one anchor and combines it with fresher data analyst, data scientist, and posted-salary signals.[13][14][15]
• Some of the June 2026 metro labor-market readings used for momentum, including unemployment and sector employment changes, are short-term estimates that may be revised later.[16][17][18][19]
• Statewide labor data was used as a proxy where metro-level occupation hiring data is not published, so the Texas Data, Analytics & AI employment and posting trends may not map perfectly to San Antonio alone.[9][10]
• The Callings.ai job database is a partial, deduplicated sample of online postings, so direction of demand, leading employer names, and skill patterns are more reliable here than exact counts or exact employer shares.[20][21][4][3]
• Several pay inputs come from salary aggregators and posted ranges collected at different times and with different methods, so use them to bracket realistic negotiations rather than to treat any single figure as the market price.[8][14][22][23][15]

References

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Live Openings in This Market

This report is published monthly; its companion page tracks the active Data, Analytics & AI openings in San Antonio-New Braunfels, TX from the live Callings.ai job index. Browse current Data, Analytics & AI openings in San Antonio-New Braunfels, TX.