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Sr. Technical Engineering Manager, Data Engineering

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Alkami Technology
Full Time position
Listed on 2026-04-25
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Alkami is the digital sales and service platform provider for U.S. banks and credit unions. Our unified Platform integrates onboarding, digital banking, and data and marketing—each solution can stand alone, but together they deliver more—to help institutions onboard, engage, and grow relationships. As the future shifts toward Anticipatory Banking, we help data-informed bankers meet the moment with technology that drives action.

Founded in 2009, we continue to be recognized for our intentional culture and tremendous growth (Best Place to Work in Fintech;
Best & Brightest to Work For Nationally; and Comparably’s Best Company Culture, Best Career Growth, Best Engineering Team, and Best Places to Work in Dallas, among others). We’re building a culture where each Alkamist can perform to their highest potential, and we’re always on the lookout for the best and brightest minds. If you’re ready to experience the power of alchemy - transforming the ordinary into the extraordinary - come join one of the fastest growing SaaS companies in the U.S.As a remote-first company, most of our positions can be remote in the US, except for key roles, which will be indicated in the Job Title.

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Dynamic role to lead the big data engineering team and drive Alkami’s data strategy forward. This role plays a pivotal part in shaping our data infrastructure enabling data-driven decision-making. This role works closely with cross-functional teams of product and engineering to design and implement scalable data platforms that drive business outcomes. This role is expected to get hands-on: 20% of your time.##

**** Essential

Duties & Responsibilities
***** Hands-On Contribution (20%)
* Team Leadership and Development:
Lead, hire, mentor, and cultivate a high-performing team of data engineers and managers. Foster a vibrant culture of collaboration, innovation, and continuous improvement, empowering the team to achieve their full potential.
* Technology Strategy and Architecture:
Take ownership of the design, development, and ongoing maintenance of scalable data systems and solutions. This includes supporting both real-time data processing for immediate insights and offline batch processing for comprehensive analysis.
* Stakeholder

Collaboration:

Work in close partnership with product managers, data analysts, and other key stakeholders. Ensure the consistent availability and impeccable quality of data to meet diverse business and operational requirements, acting as a trusted data advocate.
* Automation , Open-Source Adoption And AI workflow adoption:
Drive the automation of data processes and the development of highly scalable solutions. This will involve strategically leveraging cutting-edge open-source tools ,AI workflow and pipelining tools to maximize efficiency and flexibility.
* Data Management and Best Practices:
Continuously assess and integrate the latest data management tools, technologies, and industry best practices. Stay at the forefront of data innovation to ensure our data infrastructure remains competitive and efficient.
* Data Governance, Security, and Compliance:
Champion robust data governance practices, enforce stringent security protocols, and ensure full compliance with global industry regulations and company policies. This includes managing data access, privacy, and integrity.## ##
**** Knowledge, Skills, & Qualifications
******** Required
* **** May lead, mentor, and develop one to two Technical Engineering Managers (TEMs) and their teams.
* Built and delivered data platform for petabyte scale in fintech , banking or marktech space.
* Proven Data Architect capabilities in designing & building real time and batch processing data pipelines.
* Demonstrable hands-on experience with a comprehensive suite of data engineering tools and technologies, including but not limited to Python, PySpark SQL, Airflow, Parquet, Kafka, and Spark.
* Solid experience with leading cloud platforms such as AWS, Azure, or GCP, coupled with in-depth knowledge of big data technologies like Hadoop, Spark, metastores, and catalogs.
* A strong understanding and practical familiarity with Dev Ops practices and Continuous…
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