Americo Financial Life and Annuity Logo

Americo Financial Life and Annuity

Data Integration Developer II

Posted 2 Days Ago
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Designs, builds, and maintains batch and near-real-time data pipelines and curated datasets for insurance and annuity reporting, analytics, and business operations. Translates business requirements into integration solutions using SQL and ETL tools, implements data quality and reconciliation controls, optimizes workflows, documents lineage, and supports testing, deployment, monitoring, and issue resolution. Works independently on moderately complex pipelines while escalating architectural decisions to senior engineers or data architects.
The summary above was generated by AI

Data Integration Developer II

Job Summary:

Exists to design, build, and maintain reliable data pipelines and analytical datasets that transform insurance and annuity data into trusted assets for reporting, analytics, and business operations across Americo. This role operates with growing independence, translating business requirements into technically sound integration solutions.

Key Responsibilities

  • Develop reliable data pipelines: Design, build, and maintain batch and near-real-time data pipelines in ETL Tool and SQL that ingest, transform, and deliver insurance and annuity data accurately and efficiently for reporting, analytics, and downstream applications.

  • Translate business data needs into technical solutions: Work directly with business partners and analysts to clarify requirements, map source data to business concepts, and implement integration solutions that support underwriting, policy administration, claims, finance, and in-force management.

  • Model and prepare data for analysis: Create and maintain curated datasets, data models, and transformation logic that improve data usability, consistency, and performance for dashboards, operational reporting, and analytical use cases.

  • Ensure data quality and integrity: Implement validation checks, reconcile outputs, investigate anomalies, and resolve data issues to ensure trusted data assets and accurate information across key insurance business processes.

  • Optimize data processes for performance: Identify and implement improvements to data jobs, queries, and workflows to reduce processing time, improve reliability, and support scalable delivery of data products.

  • Document technical solutions: Produce and maintain clear documentation for data sources, transformation rules, job schedules, and business definitions so solutions are auditable, supportable, and understandable by peers.

  • Support testing, deployment, and issue resolution: Execute unit and integration testing, monitor production processes, and troubleshoot moderately complex data defects to minimize disruption to business operations.

  • Contribute to team standards: Apply established development practices, participate in peer reviews, and recommend practical improvements to tools, processes, and data management approaches.

  • Implement data quality and contract controls: Implement schema validation, business rule validation, data quality controls, and approved data contract requirements for assigned data assets.

Experience and Qualifications

  • Bachelor's degree in computer science, data engineering, information systems, or a related field, or equivalent hands-on experience.

  • 3+ years of professional experience developing and maintaining batch or near-real-time data pipelines, including production implementation of transformations, validations, and error resolution.

  • Proficient in SQL, including complex joins, aggregation, and query performance optimization.

  • Proficient in Informatica PowerCenter or equivalent ETL/ELT tool; experience with Americo's data integration environment preferred.

  • Experience with data modeling concepts and curated dataset development for reporting and analytical use cases.

Technical Competencies

  • ETL/ELT pipeline engineering: Proficiently designs, builds, and maintains batch and near-real-time ETL Tool workflows including complex transformations, error handling, restartability, and scheduling; independently resolves moderately complex pipeline issues.

  • SQL and data modeling: Writes and optimizes SQL for complex data transformations and analytical use cases; builds and maintains dimensional and relational data models that serve reporting and analytics across insurance domains.

  • Data quality and reconciliation: Implements validation rules, reconciliation checks, and monitoring logic for pipeline outputs; investigates and documents anomalies affecting financial, actuarial, and operational data.

  • Documentation and lineage: Maintains complete source-to-target mappings, transformation logic, and lineage documentation for owned assets; applies team standards consistently across all deliverables.

  • Data observability: understand pipeline monitoring, operational alerting, data reconciliation, schema validation, and basic observability practices used to maintain production data assets

Decision Making Authority

  • Selects implementation approach and data modeling strategy for assigned pipelines and datasets; escalates architectural design questions to a senior engineer or Data Architect.

  • Signs off on assigned pipeline and dataset outputs before releasing to downstream consumers; resolves routine data quality issues independently within approved boundaries.

  • Participates in decisions about coding standards and data handling practices; proposes enhancements but requires senior review before implementing changes that affect shared production environments.

Americo Values in Practice

  • Accountability: Owns the full delivery lifecycle for assigned pipelines — from requirements through testing and production monitoring — without requiring close oversight.

  • Excellence: Produces well-documented, well-tested integration solutions that downstream analytics teams can rely on without manual reconciliation or workarounds.

  • Continuous Improvement: Proactively identifies performance issues or recurring data quality patterns in owned pipelines and implements improvements that reduce incidents or processing time.

Leveling Signals

  • Independently translates a moderately complex business requirement into a reliable, well-documented pipeline solution without requiring senior engineer involvement in the design phase.

  • Consistently produces pipeline outputs that pass validation checks and are adopted into recurring reporting without material data quality follow-up from analysts or business stakeholders.

  • Identifies a recurring performance or quality issue in owned work, proposes a solution independently, and implements the fix with standard review — rather than waiting for the issue to escalate.

Similar Jobs

51 Minutes Ago
Remote or Hybrid
97K-164K Annually
Senior level
97K-164K Annually
Senior level
Aerospace • Hardware • Information Technology • Security • Software • Cybersecurity • Defense
Develop and maintain Master Data Management, data governance, stewardship, quality, and reference data processes. Partner with enterprise stakeholders and governance groups to define standards, validate master data, establish quality rules, support data owners, and prioritize initiatives. Lead requirements for system configuration changes while using data profiling, modeling, and analytics to improve data validity and consistency across systems.
Top Skills: AgileInformaticaProfiseePythonRestSemarchySoapSQL
52 Minutes Ago
Remote or Hybrid
97K-164K Annually
Senior level
97K-164K Annually
Senior level
Aerospace • Hardware • Information Technology • Security • Software • Cybersecurity • Defense
Develop and maintain master data management and integration capabilities, including data quality rules, governance processes, stewardship workflows, data validation, profiling, modeling, and integration design. Collaborate with enterprise stakeholders, data owners, stewards, and governance groups to define requirements, configure systems, and support strategic MDM initiatives. Use Python, SQL, AWS services, APIs, Dataiku, and ETL/MDM tools to improve data accuracy, consistency, transformation, and retention.
Top Skills: AgileAmazon RedshiftAPIsAws LambdaAws Step FunctionsDataikuETLInformaticaPl/SqlProfiseePythonSemarchySQL
52 Minutes Ago
Remote
USA
200K-300K Annually
Junior
200K-300K Annually
Junior
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Develop state estimation and navigation algorithms for autonomous systems operating in GPS-denied environments. Build production-grade C++ software for embedded Linux robotic platforms, create modeling and simulation tools, and implement comprehensive testing and validation. Collaborate on roadmap planning and agile execution while improving benchmarking and performance-analysis pipelines. The role requires professional C++ expertise, state estimation algorithm experience, sensor-fusion familiarity, and the ability to deploy reliable autonomy software.
Top Skills: Automated TestingBarometersC++CamerasCeresCi PipelinesEkfEmbedded LinuxGpsGraph-Based OptimizationGtsamImuLaser AltimetersMagnetometersMatlabOpenvinsParticle FiltersPythonSlamUkfVio

What you need to know about the Chicago Tech Scene

With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.

Key Facts About Chicago Tech

  • Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
  • Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
  • Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
  • Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account