Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, manage, and enhance comprehensive ETL and ELT pipelines that transition data from enterprise sources to business-ready datasets and analytical models.

• Take ownership of source connectivity, data extraction, transformation, loading, validation, storage, monitoring, recovery, documentation, and operational support.

• Assess existing pipelines, rebuild unstable or outdated processes, and choose patterns based on business value, risk, cost, performance, security, and supportability.

• Integrate SQL Server and various relational databases, ODBC sources, REST APIs, SaaS applications, secure file locations, shared datasets, CSV, JSON, Parquet, and other approved sources.

• Develop reusable ingestion patterns that address authentication, pagination, rate limits, token renewal, retries, logging, exception handling, and schema changes.

• Support batch, incremental, snapshot, near-real-time, and streaming patterns as dictated by business requirements.

• Create complex SQL queries, views, stored procedures, functions, tables, keys, and transformation logic.

• Oversee SQL Server schemas, objects, data structures, permissions coordination, backup requirements, troubleshooting, and performance optimization.

• Design normalized structures and analytical models, including facts, dimensions, star schemas, data marts, and datasets ready for semantic analysis.

• Optimize workloads through indexing, execution-plan analysis, partitioning, appropriate data types, incremental processing, and controlled historical retention.

• Construct and maintain workflows utilizing Azure Data Factory, SQL Server, and other approved tools.

• Create parameterized pipelines that incorporate retries, checkpoints, idempotency, dependency controls, backfill procedures, and failure notifications.

• Design fault-tolerant processing systems and identify, report, and resolve data errors.

• Integrate automated data-quality checks and reconcile transformed data against authoritative systems, control totals, approved reports, and business rules.

• Build and support data solutions across Microsoft Azure, Google Cloud Platform, and on-premises environments.

• Securely transfer data between environments and coordinate networking, integration runtimes, service accounts, secrets, access, and platform configuration.

• Create and manage Big Data solutions such as BigQuery and consolidate pipeline results in centralized data repositories like data lakes.

• Deliver clean, well-documented, trustworthy, and appropriately modeled data to Power BI and other reporting platforms.

• Develop reusable enterprise datasets and semantic-ready models; support relationships, field definitions, refresh requirements, and upstream performance troubleshooting.

• Safeguard customer, financial, and operational information through least privilege, role-based access, encryption, 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.

• Monitor pipelines, integrations, databases, and delivery commitments; perform root-cause analysis and implement durable corrective actions.

• Preserve architecture and data-flow diagrams, entity relationships, dictionaries, pipeline inventories, transformation specifications, validation rules, runbooks, dependencies, and recovery procedures.

• Utilize 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 to technical teams, business users, executives, vendors, and auditors.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Mathematics, Finance, or a related field; equivalent practical experience may be accepted.

• Over 3 years of relevant experience in data engineering, database development, ETL/ELT development, analytics engineering, or a closely related discipline.

• Proven ownership of production data pipelines from source ingestion through to a final analytical model or business-ready dataset.

• Experience in banking, financial services, healthcare, insurance, or another regulated industry is preferred.

• Familiarity with core systems migrations, data-platform modernization, reporting conversions, or foundational data-environment buildouts is preferred.

• Advanced SQL and T-SQL skills, including complex joins, transformations, window functions, stored procedures, query tuning, indexing, schema design, and incremental patterns.

• Demonstrated experience with CRM data streams, such as Salesforce and DataHub.

• Experience with Microsoft SQL Server from both a database and data-engineering perspective.

• Hands-on experience with Azure Data Factory or a comparable enterprise orchestration platform.

• Proficiency in Python or a similar programming language for ingestion, transformation, validation, automation, and troubleshooting.

• Knowledge of 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 performance considerations.

• Understanding of access control, encryption, logging, and auditability.

• Must be authorized to work in the U.S.; employment visa sponsorship is not available now or in the future.

• Must be able to work during Eastern Standard Hours.

• Strong knowledge of financial products and services, applicable regulations and laws, business banking products and services, and the ability to interpret financial reports and legal documents is required.

• Must be able to fulfill physical requirements including sustained standing and sitting, frequent communication and PC use, and occasional lifting of up to 20 lbs.

🏝️ Benefits

• Annual bonus, incentives, and equity may be available in addition to base salary.

• 100% employer-paid employee health coverage; employer contribution for dependents.

• Medical, Dental & Vision Insurance.

• Health Savings Account (HSA).

• Free Telemedicine access via Teladoc.

• 401(k) with 6% employer match and 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.

• 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.

• Company-Paid Life Insurance.

• Short- and Long-Term Disability Insurance.

• Voluntary Life, Accident & Critical Illness Coverage.

• Employee Assistance Program (EAP) offering free counseling, legal, and financial services.