Sr.Technical Data Engineering Manager

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 marketingeach solution can stand alone, but together they deliver moreto 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 Comparablys Best Company Culture, Best Career Growth, Best Engineering Team, and Best Places to Work in Dallas, among others). Were building a culture where each Alkamist can perform to their highest potential, and were always on the lookout for the best and brightest minds. If youre 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 Alkamis 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.

Job Title: Sr. Technical Engineering Manager Data Engineering

Position Overview We are seeking a dynamic leader to head our Big Data Engineering team and drive Alkamis data strategy forward. This role is pivotal in shaping our data infrastructure to enable datadriven decisionmaking. You will collaborate closely with product and engineering teams to design and implement scalable data platforms that deliver measurable business outcomes. The role is expected to be handson ~20% of the time.

Key Responsibilities

• HandsOn Contribution (20%): Contribute directly to design, coding, and deployment of data solutions.
• Team Leadership & Development: Lead, hire, mentor, and cultivate a highperforming team of data engineers and managers.
• Technology Strategy & Architecture: Own the design, development, and maintenance of scalable realtime and batch data systems.
• Stakeholder Collaboration: Partner with product managers, analysts, and stakeholders to ensure data availability and quality.
• Automation & AI Workflow Adoption: Drive automation of data processes, leverage opensource tools, and adopt AI workflows for efficiency.
• Data Management & Best Practices: Integrate latest tools and industry best practices to keep infrastructure competitive.
• Data Governance & Compliance: Champion governance, enforce security protocols, and ensure compliance with regulations.

Required Skills & Qualifications

• Experience leading and mentoring Technical Engineering Managers and their teams.
• Proven success building petabytescale data platforms in SaaS or Fintech companies.
• Strong Data Architect capabilities in realtime and batch pipelines.
• Handson expertise with Python, PySpark SQL, Airflow, Parquet, Kafka, Spark.
• Solid experience with AWS, Azure, or GCP, plus big data technologies (Hadoop, Spark, metastores, catalogs).
• Familiarity with DevOps practices and CI/CD pipelines for data workflows.
• Track record of managing and scaling largescale data infrastructure.
• Knowledge of data governance frameworks, quality methodologies, and security practices.
• Excellent communication skills for both technical and nontechnical audiences.
• Passion for leveraging data to drive actionable insights.

Preferred Skills

• Familiarity with AIassisted workflows (Cursor, Claude, OpenAI Codex) for coding automation and optimization.
• Experience building ingestion, ETL, or analytics platforms with AWS and opensource stacks.

Experience & Education

• Bachelors or Masters in Computer Science, Engineering, Data Science, or related field.
• 12+ years in data/platform engineering, with 5+ years in leadership roles within SaaS or Fintech organizations.