• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup

• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Apply sound version control, code review, and CI/CD practices to data workloads • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup • Contribute to architectural reviews, retrospectives, and continuous improvement of platform practices

• Partner closely with Finance/Music Ops/Acquisitions, and other business stakeholders to understand reporting needs, data gaps, and analytical requirements • Collaborate with internal data teams to translate business questions into scalable, well-modeled analytics ready data solutions • Develop, optimize, and maintain complex SQL queries and reporting tables, including recommending improvements to existing SQL data models • Analyze & integrate data from disparate data sets to develop niche reporting tables and generate meaningful insights • Apply software engineering best practices to analytics code (version control, testing, continuous integration) • Participate in code reviews, optimize SQL for performance (including Sigma-specific optimization), maintain data documentation & definitions • Other duties as assigned

About us Unifin Inc. is a global Business Process Outsourcing (BPO) company with operations across North America, Latin America, and the Asia-Pacific region. We specialize in delivering high-performance, data-driven solutions that help organizations scale, optimize operations, and drive better business outcomes. At Unifin, we pride ourselves on building a diverse, collaborative, and forward-thinking workforce—where talent is empowered to innovate, take ownership, and make real impact. We are continuously looking for exceptional individuals who are ready to grow, lead, and be part of a company that values both performance and people. ROLE SUMMARY As the Analytics Engineer, you will own the data transformation layer between the raw database and all client-facing reports. They are responsible for understanding, documenting, and modernizing the legacy stored procedure library — translating opaque SQL logic into version-controlled, tested, and maintainable data models. This is a senior role requiring both deep SQL expertise and the ability to communicate technical findings to non-technical leadership. KEY RESPONSIBILITIES - Audit, document, and map all existing stored procedures and SSIS jobs to their downstream reports and clients - Build and maintain dbt models that wrap or replace legacy stored procedures over time - Serve as the internal subject matter expert on all data transformation logic - Partner with the BI/Report Developer to ensure clean, tested data reaches Power BI - Define and enforce standards for new development — no new stored procedures created without review and approval - Identify and resolve root-cause QA issues at the data layer before reports are delivered - Present data pipeline health and migration progress to the MIS Director weekly - Maintain a documented data dictionary for all key tables, fields, and transformation rules REQUIREMENTS - 5+ years of SQL Server experience, including complex stored procedure development and optimization - Demonstrated experience reading, refactoring, or documenting legacy SQL codebases - Familiarity with dbt (Data Build Tool) or willingness to learn — dbt certification a plus - Experience with SSIS package development and troubleshooting - Ability to reverse-engineer undocumented logic and explain it clearly in plain language - Strong written communication — documentation is a core deliverable of this role - Experience in regulated industries (financial services, debt recovery, healthcare) preferred - Bachelor's degree in Computer Science, Information Systems, or equivalent experience