LendKey is on a mission to make lending simple for both lenders and borrowers. Empowering hundreds of credit unions and community banks, they connect community-based financial institutions through a robust digital network lending platform. This turnkey model enables lenders to efficiently originate loans, participate in loans from other institutions, deploy capital strategically, mitigate risk, optimize balance sheets, and enjoy the benefits of collaborative "network" lending. It provides smaller institutions with the infrastructure and scale of larger lenders while preserving their personalized, member-first values.

LendKey helps institutions originate or participate in high-quality, consumer-friendly loans across asset classes like private student loans, student loan refinancing, and home improvement financing. Through a scalable, secure digital platform, loans are sourced and serviced efficiently, letting lenders reach beyond their local markets to deploy capital effectively.

Risk mitigation is embedded in every stage, using data-driven decisioning, automated verification, and centralized servicing to maintain quality and consistency. Turnkey fractional loan participation options help lenders diversify credit risk across regions and borrower profiles, reducing exposure to local market cycles without sacrificing underwriting standards.

Beyond risk management, LendKey supports balance sheet optimization through its ALIRO platform, which democratizes loan buying and selling for institutions of all sizes while easing transaction administration.

Partnering with LendKey gives community lenders a strategic edge in digital lending without compromising their mission. For institutions seeking innovation and sustainable growth, LendKey offers the scale, security, and collaboration to lead.

The Lead Data Analyst is responsible for owning LendKey’s Sigma BI platform end-to-end, from platform administration and stakeholder partnerships to dashboard strategy and external lender reporting. This role is the primary driver of how the business consumes and acts on data.

What You'll Do:

Administer and develop the Sigma BI platform across the organization

Partner with stakeholders to understand reporting needs and translate them into scalable dashboard solutions

Plan and prioritize the reporting roadmap in collaboration with the Director of Analytics

Drive internal adoption; communicate platform capabilities, train users, and market BI as a resource

Ensure consistent KPI definitions, data accuracy, and documentation across all reporting

Own and maintain PDF-based lender reports including reconciliation, performance, and compliance call reports

Support the long-term buildout of embedded lender reporting within the Sigma platform

Collaborate with external partners and lenders on reporting requirements and delivery

Lead the migration of existing PowerBI and SSRS reports into Sigma

Prioritize migration backlog in partnership with stakeholders and the analytics team

Maintain documentation of migrated vs. outstanding reporting inventory

Ramp on LendKey’s Taktile decisioning platform through structured knowledge transfer

Progressively own maintenance of existing flows and support new flow development

Write and optimize complex SQL queries in Databricks to support reporting and analysis

Collaborate on ETL improvements and data pipeline reliability

What We’re Looking For:

4+ years of experience in data analytics, BI engineering, or a closely related field

Demonstrated experience owning a BI platform or reporting suite end-to-end; not just executing tickets

Advanced SQL expertise, particularly in Databricks or Snowflake

Strong experience with BI tools such as Sigma, Looker, Tableau, or Power BI

Proven ability to partner with business stakeholders; translating needs into solutions and driving adoption

Experience building scalable reporting frameworks rather than one-off reports

Ability to operate independently and manage competing priorities without close oversight

Experience with Sigma, Python proficiency (Pandas, PySpark, automation, or report generation)

ETL, data pipeline, or data engineering experience

Exposure to decisioning platforms or rules engines (Taktile, Drools, Blaze, Pega, or similar)

Experience with external client-facing reporting or lender reporting

Background in FinTech, lending, or financial services data