• Lead discovery & technical due diligence — get to the bottom of poorly documented legacy systems (ETL, stored procedures, reporting layers, file feeds), reconstruct the business logic, and capture it in the lineage maps, mapping specs, and risk analyses everyone builds from. • Reverse-engineer complex legacy systems using agents— you will be responsible for reverse-engineering complex, undocumented legacy systems (SSIS packages, stored procedures) where business logic is embedded, not documented. You must be able to reconstruct the intent of these systems to build modern, stable equivalents. • Drive ambiguity to resolution — spot the unknowns early, own the open questions, and pull answers from clients, SMEs, and Operations instead of waiting to be unblocked. • Architect & build the migration pipelines — turn intricate legacy logic into production-grade Airflow DAGs and Spark jobs on the Machinify platform, edge cases, payer-specific carve-outs, and business-rule exceptions included, owning the full flow from ingestion through reconciliation to steady-state handoff. • Make and document the hard architectural calls — own the decisions that matter (pipeline design, partitioning strategy, validation approach) and leave a clear trail of the reasoning so others can learn from and build on it. • Prove correctness at scale — build automated reconciliation frameworks that confirm, with confidence, that migrated output matches the source down to the row. • Own the program end to end — be the single technical owner from kickoff through go-live and hypercare: scope, sequence, and track the work, surface risks before they bite, align Operations, Client Success, Platform Engineering, SMEs, and the client, and drive UAT through to sign-off. • Raise the bar for the practice — Institutionalize migration knowledge by codifying runbooks and retrospectives, mentor L3/L4 engineers to build independent capability, and turn recurring migration pain points into scalable, reusable tooling.

Role Description This opportunity is within our Fandango group – a collection of trusted entertainment brands that guide over 50 million movie and TV fans throughout their viewing journey. Our platforms help audiences find, watch, and enjoy content with ease. Our team thrives on shaping how people discover and experience entertainment, one screen at a time. - Design and develop data pipelines, data marts, and schemas to support our data warehousing environments and analytical requirements. - Database architecture and design of data warehouses & data marts to support presentation layers, elastic cubes, reporting, and analytics. - Hands-on experience with T-SQL or PSQL development, query tuning, table development, stored procedures, functions. - Hands-on experience with creating indexes to enhance performance of workloads. - Hands-on experience with development of ETL/ELT processes; share responsibilities for monitoring the data warehouse and data marts. - Hands-on development and support of data pipelines in Airflow, AWS Glue, Azure Data Factory, Python, Golang. - Hands-on experience with cloud environments: Azure, AWS, GCP. - Troubleshoot and resolve data issues in production systems. - Communicate with business users and project managers to resolve business problems and create solutions. - Use technical experience to suggest better solutions to new and existing problems. - Involvement with other IT departments providing systems communication processes. - Meet with various IT groups to address issues/concerns, including other business unit IT groups and the technical operations group. - Mentor other Data Engineers. - Identify software solutions needed for new projects. - Weekly reporting to management on project status and issues. - On-call production support. Qualifications - 7+ years of data warehousing / OLAP experience. - 7+ years multidimensional database architecture and design experience. - 5+ years of SQL Experience. - 3+ years of Python Experience. - 2+ years of Redshift Experience. - 2+ years of NoSQL Experience. - Team and vendor partner management. - Clear understanding of principles and techniques of Web development. - Experience with AWS Glue and Airflow. - Experience with API. - Dimensional database architecture experience. - Formal systems life cycle methodology experience. Requirements - Cloud Data Warehouse operations experience. - Tableau, SSRS, big data and Realtime BI experience. - Experience with data streaming. Benefits - This position has been designated as fully remote, meaning that the position is expected to contribute from a non-Versant worksite, most commonly an employee’s residence.

• We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. • This is a player-coach role: you will architect our next-generation data stack, build proofs-of-concept (POCs), and prove out new technologies before we commit to them at scale — and you will also manage and grow a team of engineers who report directly to you. • You will partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems yourself • We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. • We also expect our engineers to work in a modern, AI-assisted way — using AI coding tools and prompt-based workflows to move faster without compromising quality. • You should be energized by evaluating tools, building POCs, and making pragmatic, evidence-based decisions about what we adopt next. • This is a build-and-prove role — you are expected to write code, design schemas, profile queries, and get into the details to understand the "how" and "why" behind every pipeline, while also mentoring your team to do the same.

• You will design, build and maintain scalable, reliable data pipelines and data platforms supporting analytical and reporting solutions • You will work on end-to-end data engineering solutions – from data ingestion, through transformation and storage, to serving curated datasets for analytics and reporting • You will develop and optimize ETL / ELT pipelines using Databricks (Apache Spark, SQL, Python) and Delta Lake technologies • You will be responsible for data modelling, data structures and performance optimization in analytical data stores (lakehouse / data warehouse) • You will implement and maintain data quality, data validation and monitoring mechanisms ensuring accuracy, consistency and reliability of processed data • You will collaborate closely with data analysts, BI developers and business stakeholders to translate business and regulatory requirements into robust technical solutions • You will contribute to architecture decisions related to data platforms, data processing patterns and technology choices • You will support and mentor junior data engineers, helping them grow their technical and consulting competencies • You will actively participate in client-facing work – discussing requirements, presenting solutions and explaining technical concepts in an accessible way • In addition to project work, you will keep up with latest data engineering, cloud and Anti Financial Crime trends and contribute to internal initiatives and accelerators.