Senior Data Engineer

Location: Onsite 3 days/week – Long Beach, CA Who We Are Provoke is a global consulting firm building AI-native solutions that transform how work gets done. Founded on a culture of innovation, growth, and curiosity, we partner with global clients to design and deploy agentic AI embedded directly into workflows so teams move faster, think smarter, and scale with purpose. Overview We're looking for a Senior Data Engineer to bring structure and technical direction to a data environment that's still taking shape. This is a senior individual contributor role, not a people management position. You'll set the technical bar for how data moves through the organization, mentor junior developers along the way, and help build the foundation for governance and integration patterns that don't fully exist yet. You'll be joining at a good moment to leave a mark, setting the strategy for scalable integration patterns, reference data models, and governance framework, while helping modernize the platform behind operational reporting, analytics, and ClientIQ. You'll have real influence over how the pieces of our evolving data architecture and systems come together. We’re looking for 1. Experience in consulting or professional services environments or similar client-facing roles. 1. Versatile people who thrive on variety and challenge. 1. Excited about working in a fast-paced environment. 1. Innate problem solvers who want to grow in a flexible, collaborative culture. 1. Takes initiative, pushes boundaries, motivated to innovate. 1. Individuals with a growth mindset who want to use their learning and relationship-building skills. 1. Proactively using Gen AI and Agents within their development process to improve quality and speed. Key Responsibilities 1. Design, build, optimize, and maintain ETL/ELT pipelines that move data reliably across the environment. 1. Develop integrations between Jack Henry Core, enterprise applications, and reporting platforms, establishing integration patterns where none currently exist. 1. Implement Change Data Capture (CDC), data reconciliation, and automated data validation across source systems. 1. Design and support enterprise data models, including dimensional, Data Vault (Hubs, Links, Satellites), semantic, master data (MDM), and reference data (RDM) models. 1. Develop orchestration workflows and automated data pipelines, using tools such as Dagster, Airflow, or Azure Data Factory, and contribute to the emerging data governance layer. 1. Mentor junior data engineers and share technical best practices across the team. 1. Troubleshoot independently and bring creative solutions to problems that don't have an obvious playbook. 1. Partner with technical and business stakeholders to translate requirements into working data solutions. 1. Optimize database and query performance across enterprise data platforms. 1. Incorporate data quality, metadata, lineage, governance, and auditability into engineering solutions. Required Skills & Experience 1. 5-8+ years of enterprise data engineering experience, including 5+ years designing ETL/ELT pipelines and data integration solutions. 1. Strong SQL and SQL Server skills, with hands-on Python experience for data engineering work. 1. Hands-on experience with workflow orchestration tools (Dagster preferred, Airflow, Azure Data Factory, or similar), along with Azure DevOps, Git, and Power BI. 1. Experience with data integration and APIs, including CDC and performance optimization. 1. Enterprise data modeling experience across dimensional, Data Vault, semantic, MDM, and RDM approaches. 1. A track record of solving problems independently, without needing a manager to point the way. 1. Experience mentoring or guiding less experienced engineers. 1. Comfort operating in ambiguity: this environment doesn't have formal patterns yet, and you'll help write them. 1. Strong communication skills, since you'll work across both technical and business audiences. Desirable Qualifications 1. Banking or financial services experience, particularly with Jack Henry or other core banking platforms. 1. Enterprise data warehouse and Customer 360 solution experience. 1. Data governance and regulatory reporting experience. 1. Microsoft certifications such as Azure Data Engineer Associate (DP-203) or Fabric Data Engineer Associate (DP-700) 1. Snowflake certifications such as SnowPro Core 1. Experience with data governance or cataloging tools (DataHub, OpenMetadata, Collibra, Alation, or similar) 1. Familiarity with additional orchestration tooling such as Prefect, beyond the core Dagster/Airflow/ADF stack 1. Experience building or maintaining a data warehouse or data mart from the ground up 1. Background establishing data quality checks, testing frameworks, or monitoring for production pipelines 1. Prior work in an environment moving from on-prem to cloud, so the candidate has lived through that kind of transition before 1. Experience introducing integration patterns or reference data practices to a team that didn't have them yet 1. Background in data mesh or domain-oriented data ownership models What success looks like You're the person the team turns to when a data problem doesn't have a clear answer yet. You've helped move the organization from ad hoc pipelines toward a repeatable, governed way of working, and junior engineers are noticeably sharper for having worked alongside you. Working Hours US time zone alignment with PT. Flexibility to accommodate client schedules is part of the role. Location US; Long Beach, CA area. Pay Range $65-90/hour Role Type & Work Authorization • This role is offered as W2 hourly employment • Candidates must be authorized to work in the U.S. without VISA Sponsorship No agencies, please. We're conducting this search internally and are not partnering with external recruiting agencies for this role. We kindly ask that agencies refrain from contacting us regarding candidate submissions.