Sr. Data Engineer

Allworth Airline Advisors (Formerly RAA); Dallas (TX); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Flexible working arrangements

401K contributions

Paid time off

Job summary

Allworth Financial is seeking a Senior Data Engineer to join the Analytics & Insights team in Addison, TX. The role will modernize legacy SQL-based processes into scalable cloud data pipelines and support a robust data analytics and reporting structure.

The ideal candidate has broad hands-on experience across data engineering, cloud data platforms, ETL/ELT, data modeling, governance, and data quality, and can design production pipelines, review architecture, and mentor the team as the data

Qualifications

• 5+ years of professional experience in data engineering, analytics engineering, data architecture, or a closely related role.
• Strong SQL skills, including stored procedures, joins, window functions, CTEs, merge logic, and performance tuning.
• Hands‑on experience with PySpark or distributed data processing frameworks.
• Experience designing and maintaining ETL/ELT pipelines in a cloud environment.

Responsibilities

• Design, build, and optimize data pipelines using PySpark, Delta Lake, SQL, and cloud-based data engineering tools.
• Improve data pipeline reliability, observability, logging, error handling, and restartability.
• Review existing notebooks, SQL scripts, data models, and orchestration workflows for maintainability and performance.
• Guide best practices for Azure Synapse, Spark, Delta Lake, data lake storage, and related cloud data services.
• Identify architectural gaps, technical debt, and modernization risks.
• Help design and implement data quality checks, reconciliation processes, and validation frameworks.
• Support development of canonical IDs, master data patterns, and entity resolution processes.
• Assist with data cataloging, lineage, metadata management, and governance practices.
• Partner with business stakeholders to understand reporting, analytics, and data product requirements.
• Help structure scalable data models for BI tools such as ThoughtSpot, Power BI, or similar platforms.
• Mentor data team members and help raise the overall engineering maturity of the team.
• Provide guidance on what we may be overlooking in areas such as security, performance, cost, governance, orchestration, testing, and long‑term maintainability.

Skills

SQL

PySpark

ETL/ELT

Delta Lake

Azure Synapse

Azure Data Factory

Data Modeling

Data Governance

Orchestration

Mentoring

Tools

Azure Synapse Analytics

Azure Data Lake Storage

Microsoft Fabric

Azure Data Factory

Job description

Summary

This is an opportunity to join a high growth business as the Data Engineer. The position will work with the Analytics & Insights team at Allworth Financial to optimize the company’s existing data infrastructure to support a robust data analytics and reporting structure.

Summary

This is an opportunity to join a high growth business as the Data Engineer. The position will work with the Analytics & Insights team at Allworth Financial to optimize the company’s existing data infrastructure to support a robust data analytics and reporting structure. We are looking for a Senior Data Engineer, or similarly experienced data modernization professional, to help guide the next stage of our data platform evolution. This role will support the modernization of legacy SQL-based processes into scalable, maintainable cloud data pipelines, while also helping us identify architectural gaps, improve engineering standards, and mature our data governance practices. The ideal candidate has broad hands‑on experience across data engineering, cloud data platforms, ETL/ELT design, data modeling, orchestration, performance tuning, data quality, and governance. We are looking for someone who can both build and advise: someone who can write production-quality pipelines, review existing architecture, mentor team members, and point out the risks, patterns, and opportunities we may not yet know to look for. This person will play a key role in helping us move from legacy stored procedures and fragmented reporting processes toward a more reliable, transparent, and well‑governed modern data architecture. This is a full‑time Exempt location. Ideal candidate will be able to work hybrid work schedule in our Addison office.

Duties And Responsibilities

• Design, build, and optimize data pipelines using PySpark, Delta Lake, SQL, and cloud-based data engineering tools.
• Improve data pipeline reliability, observability, logging, error handling, and restartability.
• Review existing notebooks, SQL scripts, data models, and orchestration workflows for maintainability and performance.
• Guide best practices for Azure Synapse, Spark, Delta Lake, data lake storage, and related cloud data services.
• Identify architectural gaps, technical debt, and modernization risks.
• Help design and implement data quality checks, reconciliation processes, and validation frameworks.
• Support development of canonical IDs, master data patterns, and entity resolution processes.
• Assist with data cataloging, lineage, metadata management, and governance practices.
• Partner with business stakeholders to understand reporting, analytics, and data product requirements.
• Help structure scalable data models for BI tools such as ThoughtSpot, Power BI, or similar platforms.
• Mentor data team members and help raise the overall engineering maturity of the team.
• Provide guidance on what we may be overlooking in areas such as security, performance, cost, governance, orchestration, testing, and long‑term maintainability.

Qualifications

• 5+ years of professional experience in data engineering, analytics engineering, data architecture, or a closely related role.
• Strong SQL skills, including stored procedures, joins, window functions, CTEs, merge logic, and performance tuning.
• Hands‑on experience with PySpark or distributed data processing frameworks.
• Experience designing and maintaining ETL/ELT pipelines in a cloud environment.
• Experience with data lake or lakehouse architecture, including Delta Lake or similar table formats.
• Strong understanding of data modeling concepts, including dimensional modeling, staging layers, curated layers, and semantic/reporting models.
• Experience with pipeline orchestration, scheduling, dependency management, and failure recovery.
• Ability to troubleshoot data quality issues, pipeline failures, schema drift, performance bottlenecks, and source system inconsistencies.
• Familiarity with modern data governance concepts, including cataloging, lineage, ownership, access control, data definitions, and data quality monitoring.
• Ability to communicate clearly with both technical and non‑technical stakeholders.
• Experience reviewing existing systems and recommending practical, incremental improvements.
• Experience with Azure Synapse Analytics, Azure Data Lake Storage, Microsoft Fabric, Azure Data Factory, or related Azure data services.

Benefits

• Medical: Blue Shield (PPOs and HDHP with HSA) plans and Kaiser (HMO) plans for California associates
• Dental insurance with MetLife
• Vision insurance with VSP
• Optional supplemental benefits
• Healthcare savings accounts with company contribution
• Flexible spending accounts
• Flexible working arrangements
• Generous 401K contributions
• Exempt associates qualify for our flexible paid time off policy
• Non‑Exempt associates will receive 15 days of paid time off annually during the first three years of employment
• 11 Paid Holidays
• Option to participate in our Equity Purchase Program (Contract, intern, and part‑time employees are not eligible)
• Future growth opportunities within the company

In addition, we work to maintain the best possible environment for our associates, where people can learn and grow with the firm. We strive to provide a collaborative, creative environment where each person feels encouraged to contribute to our processes, decisions, planning and culture.

Benefits are available to full‑time associates who work more than 30 hours a week.

The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. Typical reporting relationships are described, but actual relationships may vary in some instances. This job description is not intended to be an exhaustive list of all responsibilities, duties, skills, or knowledge required of personnel classified in this job.

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