Senior Director – Data Engineering

Fiserv

. Define and execute the strategy and roadmap for data products built on large-scale datasets .

Posted 10/16/2026full-timeAlpharetta • New Jersey • United StatesSenior💰 $145,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering teams and managing the development of scalable data products and platforms. Proficient in leveraging cloud data services, implementing CI/CD pipelines, and ensuring data quality and governance for AI-ready solutions.

Highest-signal resume keywords

Data Engineering LeadershipPython ProgrammingApache Spark ExperienceCloud Data Platforms (AWS, Azure, GCP)CI/CD and DevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Product DevelopmentData Pipeline ImplementationSQL and Data ModelingFeature EngineeringVector SearchRAG PipelinesAgile MethodologiesData Quality AssuranceCost OptimizationAutomation Best Practices

Soft Skills

Project ManagementRisk MitigationCross-Functional CollaborationCommunication SkillsTeam Leadership

Tools & Technologies

DatabricksDelta LakeUnity CatalogLakehouse ArchitectureMachine Learning Platforms

Industry Keywords

Financial ServicesData GovernanceData Mesh ApproachLarge-Scale DatasetsAI/ML Solutions

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformJavaPythonSparkSQLUnity

About the role

Key responsibilities & impact

Define and execute the strategy and roadmap for data products built on large-scale datasets
Lead and manage data engineering and development teams
Oversee the design, development, and implementation of scalable data pipelines, data platforms, and data products
Lead delivery of AI-ready data products and platform capabilities supporting machine learning and generative AI use cases, including feature engineering, vector search, and RAG pipelines
Partner with product, business, and cross-functional teams to gather requirements and translate them into data product specifications and technical solutions
Ensure data quality, reliability, security, and governance, including meeting SLAs for client data deliveries
Monitor project progress, identify risks, and implement mitigation strategies for timely and on-budget delivery
Drive performance, scalability, cost optimization, engineering best practices, automation, and release quality controls

Requirements

What you’ll need

10+ years of experience in data engineering, big data, or software development, including building data products on large-scale datasets
4+ years of experience leading data engineering or data product teams
4+ years of experience in Python, Java, or similar programming languages
4+ years of hands-on experience with Apache Spark for large-scale distributed data processing
4+ years of experience with SQL and data modeling for large, complex datasets
4+ years of experience with cloud data platforms and services on AWS, Azure, or GCP
4+ years of experience with CI/CD pipelines, DevOps/DataOps practices and Agile methodologies
Bachelor’s degree in data science, Computer Science, Engineering, Mathematics or an equivalent combination of education, work, and/or military experience
Must currently possess valid and unrestricted U.S. work authorization
Candidates requiring sponsorship now or in the future will not be considered
Experience defining and managing data products as part of a product management or data mesh approach
Experience in the financial services industry
Experience with Databricks, including Delta Lake, Unity Catalog, and Lakehouse architecture
Experience enabling AI/ML and generative AI solutions on Databricks or similar platforms, such as feature stores, vector databases, or RAG pipelines

Benefits

Comp & perks

Annual incentive opportunity, potentially delivered as a mix of cash bonus and equity awards
Approximately 10% travel off-site or to other office locations