• 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

Role Description This role is responsible for designing, building, and maintaining the data infrastructure and analytics capabilities that support supply chain and operational decision-making. The position combines hands-on data engineering, business intelligence, and system support responsibilities to ensure data is accurate, accessible, and actionable across enterprise platforms. The individual will work across systems such as ERP, project management platforms, and reporting tools to develop scalable data pipelines, dashboards, and integrations. This role bridges the gap between technical development and business operations by translating operational needs into reliable data solutions and insights. - Design, build, and maintain data pipelines and integrations across enterprise systems (ERP, project management tools, and other operational platforms). - Develop and manage data models that support reporting, analytics, and operational workflows. - Own and enhance reporting environments, including dashboards, KPIs, and self-service analytics tools (e.g., Power BI). - Ensure data accuracy, integrity, and consistency across systems through validation, monitoring, and governance practices. - Partner with Supply Chain, Finance, IT, and Operations teams to translate business requirements into scalable data and reporting solutions. - Support and optimize existing data infrastructure, including queries, transformations, and refresh processes. - Analyze operational and supply chain data to identify trends, inefficiencies, risks, and cost-saving opportunities. - Assist in the design and implementation of system workflows and integrations to improve end-to-end process efficiency. - Maintain documentation for data models, pipelines, and reporting logic to ensure transparency and auditability. - Serve as a key resource for troubleshooting data issues, reporting discrepancies, and system-related questions. - Contribute to data governance efforts, including master data management, standardization, and change control processes. - Support ad hoc data requests, analysis, and reporting needs from internal stakeholders. - Other duties as assigned. Qualifications - Bachelor’s degree in information systems, Data Analytics, Computer Science, Business, or a related field required. - 3–7 years of experience in data engineering, business intelligence, analytics, or a related role required. - Experience building and maintaining data pipelines and transformations (e.g., SQL, Power Query, Python, or similar tools) required. - Strong proficiency in data visualization and reporting tools (e.g., Power BI, Tableau). - Experience working with ERP or operational systems (NetSuite, Salesforce, SAP, Oracle, or similar). - Solid understanding of data modeling concepts and relational databases. - Strong analytical and problem-solving skills with attention to detail. - Ability to translate business requirements into technical solutions and actionable insights. - Experience working in cross-functional environments with both technical and non-technical stakeholders. - Familiarity with data governance, data quality, and validation best practices preferred.