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Senior Analytics Engineer - On-Site (Texas)

Pay
Pay not listedSimilar roles state $122K–$190K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting

What you’ll work on

Full posting
  • Build and maintain ELT pipelines with Fivetran or similar tools

  • Develop and own dbt projects, including models, tests, and semantic layer

  • Own Snowflake architecture, access control, warehouses, and cost governance

  • Define data quality standards and build data lineage documentation

From the employer’s posting
Designs, builds, and maintains scalable ELT pipelines using Fivetran or similar ingestion tools
Develops and owns dbt projects, including data models, tests, documentation, and semantic layer definitions.
with individual accountability for areas including database and schema design, role-based access control (RBAC), virtual warehouse management, cost governance, and performance optimization.
Defines and enforces data quality standards through dbt tests, monitoring pipelines, and data observability practices.
Apply at Southside Bancshares

Posting record

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Actively hiringFirst seen by us 11 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 24, 202611 days ago
Recorded sightings
14
Last seen by us
Nov 3, 2026
Employer says posted
Oct 22, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$122K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 321 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 11

Similar jobs usually come down between day 6 and day 47.

From 1,405 similar postings that came down. Coming down is not always a hire.

Southside Bancshares is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Airbyte
  • dbt
  • Fivetran
  • Snowflake
Where the posting names them
- Familiarity with Snowflake Cortex and AI/ML features, including LLM functions, document AI, and Snowpark. - Experience with Python for data engineering tasks, including Snowpark Python preferred. - Working knowledge of data modeling concepts including dimensional modeling (Kimball), Data Vault, and medallion architecture.
- Deep expertise in Snowflake, including virtual warehouses, Snowpipe, Streams and Tasks, RBAC, clustering, and cost optimization. - Advanced SQL skills and strong proficiency in dbt (data build tool), including Jinja templating, materializations, and incremental models. - Familiarity with Snowflake Cortex and AI/ML features, including LLM functions, document AI, and Snowpark.
- Demonstrated experience building and maintaining dbt projects in a production environment, including models, tests, macros, and documentation. - Experience with data ingestion tools such as Fivetran, Airbyte, or comparable ELT platforms. - Experience in banking, financial services, or a similarly regulated industry preferred.
Job Summary: The Senior Analytics Engineer is a senior technical role within Southside Bank’s data team, focused on building and maintaining the Snowflake data platform that supports analytics, reporting, and AI capabilities across the organization. This person will lead day-to-day work across data ingestion, dbt modeling, and data quality, and will be the team’s primary resource on Snowflake AI and Cortex features. Platform decisions are made collaboratively as a team, with this role carrying individual accountability for specific workstreams and initiatives. Essential Functions:
- Designs, builds, and maintains scalable ELT pipelines using Fivetran or similar ingestion tools to bring new data sources into the Snowflake environment. - Develops and owns dbt projects, including data models, tests, documentation, and semantic layer definitions. - Contributes to the architecture and maintenance of the Snowflake environment, with individual accountability for areas including database and schema design, role-based access control (RBAC), virtual warehouse management, cost governance, and performance optimization.
- Partners with business units, compliance, finance, and operations teams to understand data requirements and translate them into documented data models. - Defines and enforces data quality standards through dbt tests, monitoring pipelines, and data observability practices. - Builds and maintains data lineage documentation to ensure transparency and traceability across the data platform.
- Supports the development of dashboards, self-service analytics tools, and reporting layers used by business stakeholders across the Bank. - Monitors Snowflake platform releases, dbt updates, and developments in financial services AI/ML to evaluate applicability to the Bank’s environment. - Maintains confidentiality of all sensitive Bank information.
- 3+ years of hands-on, production-level Snowflake experience required; SnowPro Core or Advanced certification is a strong plus. - Demonstrated experience building and maintaining dbt projects in a production environment, including models, tests, macros, and documentation. - Experience with data ingestion tools such as Fivetran, Airbyte, or comparable ELT platforms.
Essential Functions: - Designs, builds, and maintains scalable ELT pipelines using Fivetran or similar ingestion tools to bring new data sources into the Snowflake environment. - Develops and owns dbt projects, including data models, tests, documentation, and semantic layer definitions.
- Develops and owns dbt projects, including data models, tests, documentation, and semantic layer definitions. - Contributes to the architecture and maintenance of the Snowflake environment, with individual accountability for areas including database and schema design, role-based access control (RBAC), virtual warehouse management, cost governance, and performance optimization. - Serves as the team’s lead on Snowflake AI and Cortex features, driving the implementation of LLM-powered analytics, document intelligence, and AI-driven workflows in partnership with business stakeholders and teammates.
- Contributes to the architecture and maintenance of the Snowflake environment, with individual accountability for areas including database and schema design, role-based access control (RBAC), virtual warehouse management, cost governance, and performance optimization. - Serves as the team’s lead on Snowflake AI and Cortex features, driving the implementation of LLM-powered analytics, document intelligence, and AI-driven workflows in partnership with business stakeholders and teammates. - Partners with business units, compliance, finance, and operations teams to understand data requirements and translate them into documented data models.
- Minimum of 5 years of experience in data engineering, analytics engineering, or a closely related data role; 8+ years preferred. - 3+ years of hands-on, production-level Snowflake experience required; SnowPro Core or Advanced certification is a strong plus. - Demonstrated experience building and maintaining dbt projects in a production environment, including models, tests, macros, and documentation.
Necessary Skills: - Deep expertise in Snowflake, including virtual warehouses, Snowpipe, Streams and Tasks, RBAC, clustering, and cost optimization. - Advanced SQL skills and strong proficiency in dbt (data build tool), including Jinja templating, materializations, and incremental models.
- Advanced SQL skills and strong proficiency in dbt (data build tool), including Jinja templating, materializations, and incremental models. - Familiarity with Snowflake Cortex and AI/ML features, including LLM functions, document AI, and Snowpark. - Experience with Python for data engineering tasks, including Snowpark Python preferred.

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About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Position Title: 

Senior Analytics Engineer

FSLA Status: 

Exempt (17C)

Reports to: 

Director of Data Analytics and Strategy

Location:

Tyler or Dallas Fort Worth, Texas

  • Only Candidates currently residing in the Texas area will be considered.  No relocation assistance or fully remote options available.
  • Open to a hybrid work schedule - 3 days in the office/2 days working from home. 

Job Summary:

The Senior Analytics Engineer is a senior technical role within Southside Bank’s data team, focused on building and maintaining the Snowflake data platform that supports analytics, reporting, and AI capabilities across the organization. This person will lead day-to-day work across data ingestion, dbt modeling, and data quality, and will be the team’s primary resource on Snowflake AI and Cortex features. Platform decisions are made collaboratively as a team, with this role carrying individual accountability for specific workstreams and initiatives. 

Essential Functions:

  • Designs, builds, and maintains scalable ELT pipelines using Fivetran or similar ingestion tools to bring new data sources into the Snowflake environment.
  • Develops and owns dbt projects, including data models, tests, documentation, and semantic layer definitions.
  • Contributes to the architecture and maintenance of the Snowflake environment, with individual accountability for areas including database and schema design, role-based access control (RBAC), virtual warehouse management, cost governance, and performance optimization.
  • Serves as the team’s lead on Snowflake AI and Cortex features, driving the implementation of LLM-powered analytics, document intelligence, and AI-driven workflows in partnership with business stakeholders and teammates.
  • Partners with business units, compliance, finance, and operations teams to understand data requirements and translate them into documented data models.
  • Defines and enforces data quality standards through dbt tests, monitoring pipelines, and data observability practices.
  • Builds and maintains data lineage documentation to ensure transparency and traceability across the data platform.
  • Evaluates and onboards new data sources, collaborating with source system owners to ensure reliable, timely, and accurate data delivery.
  • Supports the development of dashboards, self-service analytics tools, and reporting layers used by business stakeholders across the Bank.
  • Monitors Snowflake platform releases, dbt updates, and developments in financial services AI/ML to evaluate applicability to the Bank’s environment.
  • Maintains confidentiality of all sensitive Bank information.
  • Maintains a positive and caring atmosphere for customers and employees consistent with Southside Bank’s mission, CORE Values, and Blue Book culture guide.
  • Provides enthusiastic, professional, and courteous service to Southside Bank customers and employees.
  • Participates in proactive team efforts to achieve departmental and company goals.
  • Understands and agrees to abide by the policies and procedures established at Southside Bank.
  • Responsible for complying with audit policies and procedures as they pertain to this position.
  • Performs duties in compliance with applicable laws and regulations, including but not limited to the Bank Secrecy Act (BSA) and related anti-money laundering laws, and in accordance with the Bank’s Information Security Program.
  • Must comply with all applicable laws and regulations.

Additional Functions:

  • Provides leadership to others through example and sharing of knowledge/skill.
  • Complies with all safety policies, practices, and procedures. Report all unsafe activities to supervisor and/or Human Resources.
  • Performs additional duties, as assigned or directed.

Required Education/Experience:

  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field preferred; equivalent work experience considered.
  • Minimum of 5 years of experience in data engineering, analytics engineering, or a closely related data role; 8+ years preferred.
  • 3+ years of hands-on, production-level Snowflake experience required; SnowPro Core or Advanced certification is a strong plus.
  • Demonstrated experience building and maintaining dbt projects in a production environment, including models, tests, macros, and documentation.
  • Experience with data ingestion tools such as Fivetran, Airbyte, or comparable ELT platforms.
  • Experience in banking, financial services, or a similarly regulated industry preferred.

Necessary Skills:

  • Deep expertise in Snowflake, including virtual warehouses, Snowpipe, Streams and Tasks, RBAC, clustering, and cost optimization.
  • Advanced SQL skills and strong proficiency in dbt (data build tool), including Jinja templating, materializations, and incremental models.
  • Familiarity with Snowflake Cortex and AI/ML features, including LLM functions, document AI, and Snowpark.
  • Experience with Python for data engineering tasks, including Snowpark Python preferred.
  • Working knowledge of data modeling concepts including dimensional modeling (Kimball), Data Vault, and medallion architecture.
  • Experience integrating and working with financial data systems (core banking, loan origination, general ledger, ACH, wire) is a plus.
  • Strong understanding of data governance, data quality, and data lineage best practices.
  • Working knowledge of model risk management (MRM) principles, including model validation, documentation, and governance requirements applicable to financial institutions.
  • Familiarity with data privacy principles and requirements applicable to financial institutions, including internal data classification and handling standards.
  • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical business stakeholders.
  • Ability to work independently and take ownership of specific domains and initiatives within a small, collaborative team environment.
  • Comfortable working in a fast-moving, regulated environment with evolving business priorities.
  • Able to develop and sustain sound working relationships and credibility at all levels within the organization.
  • Ability to solve practical problems and deal with a variety of concrete variables in situations where only limited standardization exists.

 Physical Activity/Dexterity:

  • Manual dexterity sufficient to reach/handle items and work with fingers. Works with fingers and perceives attributes of objects and materials.

Physical Environment Demands:

  • Must be able to remain in a stationary position 90% of the time.
  • The person in this position needs to occasionally move about inside the office to visit other offices, conference rooms, office machinery, etc.
  • Constantly operates a computer and other office productivity machinery, such as a calculator, copy machine, and telephone.
  • Constantly positions self to operate on a computer.
  • The person in this position frequently communicates with other people throughout each day. Must be able to exchange accurate information when conversing.

Work Schedule/Hours:

  • Monday through Friday; 8:00am – 5:00pm.
  • On call for planned after-hours deployments, system changes, and critical project support, as needed.
  • Available for overtime, as needed.

 Travel:

  • Minimal overnight travel (up to 10%) by land and/or air.

Southside Bank uses E-Verify to confirm the employment eligibility of all newly hired employees. 

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)

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Location & working pattern

Tyler, TX, US

Tyler or Dallas Fort Worth, Texas - Only Candidates currently residing in the Texas area will be considered. No relocation assistance or fully remote options available. - Open to a hybrid work schedule - 3 days in the office/2 days working from home. Job Summary:
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