Remote Backend Data Engineer – Ukraine
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Build scalable data pipelines, models, and backend infrastructure for evolving data products. Work with dbt, Snowflake, Databricks, orchestration platforms, and GenAI engineering tools.
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Oportun is a fintech company focused on making everyday financial tools more accessible. Its products include personal loans from $300 to $10,000, savings solutions, and an app that helps customers manage borrowing and save money. Oportun also provides financial education, loan calculators, and prequalification tools designed to help people explore options without affecting their credit score. The company works with partner banks to provide FDIC-insured deposit accounts and has a team of more than 1,000 employees across fintech, insurance, and consulting.
Senior Data Engineer – Databricks (India Remote)
Lead secure Databricks data products and lakehouse infrastructure for Oportun’s financial services operations in India. Own architecture, production pipelines, governance, integrations, and member communications data.
Description
- Build and operate secure, scalable data products for audience selection, eligibility, preferences, consent, campaign inputs, delivery data, and operational reporting.
- Define secure data architectures, including models, contracts, lineage, and ownership standards.
- Own complex data engineering initiatives from technical discovery and design through production release.
- Coordinate engineers and stakeholders while managing dependencies, risks, and technical decisions.
- Develop and optimize production pipelines and integrations with Databricks, Apache Spark, PySpark, Spark SQL, Delta Lake, and SQL.
- Modernize suitable legacy data workloads.
- Implement reliable patterns for data loading, reconciliation, retries, idempotency, recovery, and deployment.
- Maintain lakehouse and operational data assets for performance, integrity, availability, and security.
- Establish data-quality and governance controls through validation, monitoring, alerting, dashboards, runbooks, and lineage.
- Work with Privacy, Compliance, Risk, and Security teams on PII, consent, preferences, suppression, retention, and access controls.
- Provide technical direction through design and code reviews, mentor junior engineers, and lead complex production investigations.
- Trace incidents to their root causes and deliver lasting corrective solutions.
- Collaborate with Product, Communications, Analytics, Engineering, Risk, Privacy, Compliance, and other partners.
- Prepare releases through automated testing, CI/CD, rollout planning, and post-release measurement.
- Track pipeline performance, quality, timeliness, cost, and reliability.
- Apply AI tools judiciously to reduce repetitive work and strengthen engineering decisions.
Requirements
- At least six years of data engineering experience spanning architecture, pipelines, platforms, and database or lakehouse operations.
- Bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or a related discipline, or equivalent practical experience.
- Advanced working proficiency in Python, PySpark, and SQL.
- Demonstrated leadership, analytical problem-solving, sound judgment, and clear communication.
- Production experience with Databricks, Apache Spark, Spark SQL, Delta Lake, workflow orchestration, CI/CD, Git workflows, automated testing, and end-to-end data integrations or products.
- Background in data quality, observability, alerting, lineage, and cloud services, particularly AWS.
- Experience securing sensitive member data through access controls, secrets management, encryption, and auditability, along with experience in Agile delivery.
- Experience in financial services, lending, marketing technology, customer communications, or another regulated sector.
- Familiarity with Unity Catalog or similar governance platforms, plus Java or Scala.
- Experience applying tools such as ChatGPT or Copilot to engineering productivity, testing, documentation, troubleshooting, data quality, or operations.
- Awareness of AI agents or automations, with careful judgment around security, privacy, accuracy, and human oversight.
Benefits
- Medical, dental, and vision insurance.
- Provident Fund.
- Life and accident insurance.
- Internet allowance.
- Fuel allowance.
- Meal allowance.
- Telephone allowance.
- Compensation and benefits package designed to support physical, financial, and professional well-being.
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