• Design, build, and maintain batch, incremental, and file-based data pipelines to support analytics, reporting, and operational use cases. • Support data migration initiatives, including the movement of data from legacy systems to modern platforms, ensuring continuity, accuracy, and reconciliation. • Work with enterprise data integration tools such as Talend, including maintaining existing Talend jobs and supporting the migration or re-implementation of Talend pipelines into other platforms where required. • Establish and maintain a robust data engineering environment (e.g., dev/test/prod separation, access controls, naming standards, source control, deployment processes, and monitoring) that enables reliable delivery and safe change management. • Support ingestion, storage, and management of unstructured and semi-structured datasets (e.g., documents, PDFs, text extracts, files, metadata) alongside traditional relational data. • Support and optimize data models in Power BI dashboards and AI-enabled analytics. • Prepare and curate analytics- and AI-ready datasets, including clean, well-defined tables and reference data used in automation and AI-enabled solutions. • Collaborate closely with AI & Automation Specialists to ensure data requirements for AI initiatives are well understood, properly sourced, validated, and production-ready. • Translate business and reporting requirements into scalable data models, transformations, and pipeline designs. • Develop and maintain trusted datasets that support dashboards, scorecards, client reporting, and downstream analytics. • Implement data quality checks, validation logic, reconciliation processes, and monitoring to ensure data reliability and consistency. • Troubleshoot and resolve data issues across ingestion, transformation, and consumption layers, identifying root causes and remediation actions. • Develop and maintain clear documentation, including source-to-target mappings, data definitions, data lineage, and known limitations. • Work in partnership with analytics, IT, data governance, and security stakeholders to ensure data solutions comply with privacy, security, and regulatory expectations. • Contribute to the prioritization, planning, and delivery of multiple data engineering, migration, and enablement initiatives in parallel.

• Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization. • Build and implement scalable solutions that align to our data governance standards and architectural roadmap for data integrations, data storage, reporting, and analytic solutions. • Design, develop and test data integration solutions. Write, automate and document unit/integration/functional tests. • Manage automated deployments using Git pipelines, ensuring code changes are efficiently version-controlled and deployed. • Collaborate with multiple teams to streamline deployment workflows, monitor and troubleshoot pipelines for reliability and performance. • Perform data analysis required to troubleshoot data-related issues by building a data quality framework and assist in the resolution of data issues. • Serve as tech lead by mentoring less experienced members of the team through code reviews, pair programming and similar hands-on interactions.

• Design, build, and maintain a simple, effective, and scalable data warehouse on Snowflake — with clean models, well-named fields, and documentation that makes the warehouse easy to use by downstream users and systems • Implement and manage data transformation with dbt to ensure reliable, well-tested pipelines • Develop and evolve data models, semantic layers, and metric definitions that support a wide range of business needs while keeping data consistent and accurate across the organization • Own data quality, observability, and testing that protects downstream consumers from broken or misleading data • Build and evolve internal AI tooling (skills, agents, etc) that makes the Data Engineering team more effective • Partner with analysts, product engineers, and business stakeholders to understand their needs, scope the right solution, and deliver outcomes • Mentor analysts and peers, fostering a culture of learning, rigor, and continuous improvement • Proactively identify operational issues and propose evolutionary solutions

Role Description We are looking for a Data Engineer to support a strategic data platform migration, moving tables, views, and stored procedures from Amazon Redshift to Databricks. You will build and support Databricks pipelines and jobs, work with AWS services including S3, Glue, and Athena, and apply data governance practices including data lineage, cataloging, and role-based access controls throughout the migration. This is a 5–6 month project engagement. What You Will Do - Migrate tables, views, and stored procedures from Amazon Redshift to Databricks. - Build and support Databricks pipelines and jobs. - Work with AWS services, including Amazon S3, AWS Glue, and Amazon Athena. - Support data migration activities within a modern data lake architecture. - Apply data governance and data management practices throughout the migration. - Collaborate with project stakeholders to support migration activities. Qualifications - 3–5 years of experience as a Data Engineer. - Hands-on experience with Databricks. - Experience with Amazon Redshift. - Strong SQL skills. - Experience with AWS services, including Amazon S3, AWS Glue, and Amazon Athena. - Experience building and supporting Databricks pipelines and jobs. - Understanding of data lake architectures. - Familiarity with data governance and data management practices, including data lineage, data catalogs, and role-based access controls (RBAC). - Upper-intermediate English level. Nice to Haves - Experience with Databricks Lakebridge transpiling capabilities. Benefits - Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget. - Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews. - Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm. - Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands. - Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized. - Well-being & support: access local well-being programs and people-focused support tailored to your location.