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Climate First Bank

Bank offering solar and green loans

Data Engineer

Data EngineeringUpdated on Nov 11
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, Finance, or a related field, or equivalent practical experience.
  • At least 2 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.
  • SQL and T-SQL skills, including complex joins, transformations, window functions, stored procedures, query tuning, indexing, schema design, and incremental patterns.
  • Demonstrated experience modeling and integrating CRM data streams such as Salesforce and DataHub.
  • Microsoft SQL Server experience from a database and data-engineering perspective.
  • 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, upstream performance considerations, access control, encryption, logging, and auditability.
  • Banking, financial services, healthcare, insurance, or other regulated-industry experience is preferred in the posting but listed as experience context.
  • Core systems migration, data-platform modernization, reporting conversion, or foundational data-environment buildout experience is preferred in the posting but listed as experience context.
  • Ability to communicate scope, dependencies, risks, limitations, timelines, and recovery status clearly to technical teams, business users, executives, vendors, and auditors.
  • Ability to interpret financial reports and legal documents, with knowledge of financial products, services, applicable regulations, and laws.
  • Willingness to work Eastern Standard Hours in a remote role within the United States.
  • Ability to perform sustained standing and sitting, frequent communication and computer use, and occasional lifting up to 20 pounds.

Responsibilities

  • 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 business needs, balance immediate delivery with a scalable foundation, and avoid unnecessary complexity.
  • Evaluate existing pipelines, rebuild unstable or obsolete processes, and select patterns based on business value, risk, cost, performance, security, and supportability.
  • 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.
  • 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.
  • 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.
  • 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, late-arriving 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 and maintain traceability for exceptions, remediation, and reprocessing.
  • 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 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, and avoid unnecessary replication when secure direct-query or shared-data approaches are appropriate.
  • Create and work with Big Data solutions and products such as BigQuery, and consolidate pipeline results on centralized data stores such as data lakes.
  • Deliver clean, documented, trustworthy, 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.
  • 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, and escalate suspected control failures or unauthorized access.
  • 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.

Desired Qualifications

  • Experience in banking, financial services, healthcare, insurance, or another regulated industry.
  • Experience with core systems migrations, data-platform modernization, reporting conversions, or foundational data-environment buildouts.

About the Company

Climate First Bank

Bank offering solar and green loans

Climate First Bank is a full-service bank focused on helping customers make environmentally friendly financial decisions. Its products include personal loans for solar installations and energy retrofits, commercial loans, and standard banking services like checking and savings accounts. The bank emphasizes a simple, fast experience for solar financing, offering quick approvals, competitive interest rates, and no dealer fees. It differentiates itself by prioritizing sustainability and community impact, including pursuing a LEED-certified branch and leadership that aims to direct deposits toward planet-saving investments. The bank's goal is to earn profit while delivering a positive environmental impact for Central Floridians and their stakeholders.

Company size
51-200
Company stage
Series A
Total funding
$148M
Headquarters
Saint Petersburg, Florida
Founded
2020

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