Data Engineer

We are changing FINANCE to finance CHANGE!

At Climate First Bank, we’re redefining what banking can be. As a Florida Benefit Corporation and FDIC-insured commercial bank, we offer a full suite of personal and business services—including solar, residential, commercial, ESOP Banking, Structured Finance and SBA loans—all designed to power a better future. We’re proud to be a Certified B Corporation, a member of 1% for the Planet, and part of the Global Alliance for Banking on Values (GABV), reflecting our deep commitment to sustainability, transparency, and ethical banking.

With branches in St. Petersburg, Winter Park, Mount Dora, and a growing digital presence, we’re proving that banking can be a force for good. We don’t just support environmental and social causes—we’re built on them.

Under our Holding Company, Climate First Bancorp, we are also powered by OneEthos. OneEthos operates at the intersection of fintech and traditional banking to expand access to inclusive, values-driven financial services. Regulated by the Federal Reserve Bank, it equips Community Banks, Credit Unions, CDFIs, and Green Banks with ethical lending tools—especially in climate finance and solar lending.

Join the Movement

We’re seeking driven, mission-aligned individuals ready to make an impact. If you’re passionate about sustainability, thrive in a fast-paced, results driven environment, and want to be part of something bigger, you will feel right at home.

Our team is one of goal-setters, go-getters, problem solvers, thought leaders, and changemakers. We celebrate wins, tackle challenges head-on, and push boundaries. Fueled by purpose, we thrive where perseverance and passion turn ambitious goals into reality.

Thrive at Climate First Bank

At Climate First Bank, we’re investing in your future. We offer a comprehensive, people-first benefits package that supports your health, finances, and work-life balance. Please note that benefit eligibility varies by employment status and that benefits for part-time employees may differ from those listed below.

Compensation — In addition to the base salary, this position may be eligible for an annual bonus, incentives and equity. Actual compensation is based on industry salary ranges, internal salary structures, experience, skills and other job-related factors.

Health Coverage — 100% employer-paid for employees; employer contribution for dependents by Us

• Medical, Dental & Vision Insurance
• Health Savings Account (HSA)
• Free Telemedicine access via Teladoc

Financial Wellness & Wealth Building

• 401(k) with 6% Employer Match — No Vesting Period.
• Employee Stock Options
• Exclusive Employee Banking Perks
• 0% Financing for Employee Solar Loans
• Employee Only Mortgage Product with exclusive interest rates and terms.
• 0% Financing for Eligible Electric Vehicles (EVs)
• Referral Incentives

Generous Paid Time Off

• 2–4 Weeks of Vacation based on officer level plus additional tenure-based time.
• 64 Hours of Paid Sick Time for all full-time employees.

Protection & Peace of Mind

• Company-Paid Life Insurance
• Short- & Long-Term Disability Insurance
• Voluntary Life, Accident & Critical Illness Coverage
• Employee Assistance Program (EAP) with free counseling, legal, and financial services.

Now Hiring: Data Engineer

All Climate First Bank employees must be willing to embrace the vision of an inclusive, equitable, and regenerative economic system. The Data Engineer designs, builds, maintains, and improves the Bank’s enterprise data pipelines, integrations, databases, and analytical data models. The role owns the flow of data from source connection through ingestion, transformation, validation, storage, monitoring, and delivery to reporting and analytics consumers. This hands-on role spans cloud, on-premises, and hybrid environments. The Data Engineer integrates core banking platforms, operational databases, APIs, files, SaaS applications, and cloud data platforms while emphasizing secure, reliable, documented, and business-ready outcomes. The successful candidate must combine strong SQL, data integration, scripting, data quality, and troubleshooting skills with practical judgment and clear communication.

What You’ll Contribute as a Data Engineer

Data Architecture and Pipeline Ownership

• Design, develop, operate, and improve end-to-end ETL and ELT pipelines from enterprise sources to business-ready datasets and analytical models.
• Own source connectivity, extraction, transformation, loading, validation, storage, monitoring, recovery, documentation, and operational support.
• Build maintainable solutions that meet defined business needs without unnecessary complexity; balance immediate delivery with a scalable foundation.
• Evaluate existing pipelines, rebuild unstable or obsolete processes, and select patterns based on business value, risk, cost, performance, security, and supportability

Data Integration and Source Connectivity

• Integrate Microsoft SQL Server and other relational databases, ODBC sources, REST APIs, SaaS applications, secure file locations, shared datasets, CSV, JSON, Parquet, and other approved sources.
• Develop reusable ingestion patterns for authentication, pagination, rate limits, token renewal, retries, logging, exception handling, and schema changes.
• Support batch, incremental, snapshot, near-real-time, and streaming patterns when justified by business requirements.
• Maintain source-to-target mappings and document how source fields become standardized, validated, and usable information.

SQL, Database Engineering, and Data Modeling

• Create complex SQL queries, views, stored procedures, functions, tables, keys, and transformation logic.
• Manage SQL Server from the database perspective, including schemas, objects, data structures, permissions coordination, backup requirements, troubleshooting, and performance.
• Design normalized structures and analytical models, including facts, dimensions, star schemas, data marts, and semantic-ready datasets.
• Optimize workloads through indexing, execution-plan analysis, partitioning, appropriate data types, incremental processing, and controlled historical retention.

ETL/ELT Development and Reliability

• Build and maintain workflows using approved platforms such as Azure Data Factory, SQL Server, and other Bank-approved tools.
• Determine when to use full loads, incremental loads, watermarks, change tracking, snapshots, or event-driven patterns.
• Create parameterized pipelines with retries, checkpoints, idempotency, dependency controls, backfill procedures, and failure notifications.
• Design fault-tolerant processing so isolated data errors are captured and reported without unnecessarily stopping unrelated workloads.

Data Quality, Validation, and Reconciliation

• Embed automated checks for schema, data types, required fields, ranges, reference values, row counts, totals, balances, and completeness.
• Detect and handle duplicates, null values, malformed identifiers, invalid formats, latearriving records, schema drift, and incorrect aggregates.
• Reconcile transformed data against authoritative source systems, control totals, approved reports, and business rules.
• Prevent unverified data from reaching production reporting layers; maintain traceability for exceptions, remediation, and reprocessing.

Cloud, Hybrid, Performance, and Cost

• Build and support data solutions across Microsoft Azure, Google Cloud Platform, and on-premises environments as required by the Bank’s architecture.
• Securely move data between environments and coordinate on networking, integration runtimes, service accounts, secrets, access, and platform configuration.
• Improve execution time, query performance, freshness, reliability, and resource use through batching, parallelism, partitioning, workload management, and incremental processing.
• Assess storage, compute, movement, licensing, and duplication costs before changes; avoid unnecessary replication when secure direct-query or shared-data approaches are appropriate.

Data Consolidation and Big Data

• Be capable of creating and working with Big Data solutions and products, such as BigQuery.
• Consolidate pipelines results on centralized data stores such as Datalakes and others.

Analytics and Power BI Readiness

• Deliver clean, documented, trustworthy, and appropriately modeled data to Power BI and other approved reporting platforms.
• Build reusable enterprise datasets and semantic-ready models; support relationships, field definitions, refresh requirements, and upstream performance troubleshooting.
• Partner with analysts and reporting teams while maintaining clear ownership boundaries between engineering, analytical modeling, and visualization development.

Security, Governance, and Compliance

• Protect customer, financial, and operational information through least privilege, role-based access, encryption, approved secret management, logging, monitoring, and separation of duties.
• Maintain lineage, metadata, ownership, classification, retention, and access documentation; support audits, risk assessments, vendor reviews, and examinations.
• Ensure solutions align with Bank policies and applicable expectations, including GLBA, FFIEC, NIST, BSA, AML, CIP, and OFAC; escalate suspected control failures or unauthorized access.

Operations, Documentation, and Collaboration

• Monitor pipelines, integrations, databases, and delivery commitments; perform root-cause analysis and implement durable corrective actions.
• Maintain architecture and data-flow diagrams, entity relationships, dictionaries, pipeline inventories, transformation specifications, validation rules, runbooks, dependencies, and recovery procedures.
• Use approved shared repositories, version control, peer review, controlled releases, and change management for SQL, Python, pipeline assets, and documentation.
• Gather requirements and communicate scope, dependencies, risks, limitations, timelines, and recovery status clearly to technical teams, business users, executives, vendors, and auditors.

What You’ll Leverage in this Role:

Experience & Education

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, Finance, or a related field; equivalent practical experience may be considered.
• 3+ years of relevant experience in data engineering, database development, ETL/ELT development, analytics engineering, or a related discipline.
• Demonstrated ownership of production data pipelines from source ingestion through a final analytical model or business-ready dataset.
• Experience in banking, financial services, healthcare, insurance, or another regulated industry is preferred.
• Experience with core systems migrations, data-platform modernization, reporting conversions, or foundational data-environment buildouts is preferred.

Required Technical Skills

• Advanced SQL and T-SQL, including complex joins, transformations, window functions, stored procedures, query tuning, indexing, schema design, and incremental patterns.
• Demonstrated experience with CRM data streams (modeling and integration), like Salesforce and DataHub.
• Microsoft SQL Server experience from a database and data-engineering perspective.
• Hands-on experience with Azure Data Factory or a directly comparable enterprise orchestration platform.
• Proficiency in Python or an equivalent language for ingestion, transformation, validation, automation, and troubleshooting.
• Experience with APIs, file-based data, hybrid integration, analytical modeling, automated quality controls, monitoring, recovery, Git-based version control, and production support.
• Working knowledge of Power BI data models, relationships, refresh patterns, and upstream performance considerations