Mid Data Migration Engineer

KEY RESPONSIBILITIES** **Pipeline Design & Development** - Design, develop, and maintain production-grade ELT pipelines, applying data engineering best practices and engineering rigour throughout. - Build and manage data loading processes for distributed storage systems — both relational and non-relational. - Aggregate and transform large-scale datasets using distributed processing tools (Spark, Kafka, Presto, or equivalent). **Infrastructure & Automation** - Provision and maintain data infrastructure using Infrastructure as Code (IaC) tooling, primarily Terraform. - Automate infrastructure lifecycle management to ensure scalability, reliability, and security standards are consistently met. **Reliability & Governance** - Own SLA monitoring for data pipelines, proactively identifying and resolving issues in cloud and on-premises environments. - Implement data access policies and quality standards in line with client governance requirements. **Collaboration & Influence** - Partner with analysts, architects, and client stakeholders to translate business requirements into sound technical solutions. - Contribute to technical decision-making, challenging approaches constructively and proposing improvements with supporting rationale. - Support the professional growth of junior engineers through code review, pairing, and knowledge sharing. **Research & Innovation** - Evaluate and introduce tools or technologies that improve the efficiency, reliability, or scalability of data platforms. - Document architectures, patterns, and processes to build a durable knowledge base for the team and clients. ## Requirements * * * At Indicium AI we believe in personal growth and professional development, and are convinced that the perfect candidate is one that continuously learns. Therefore, these requirements are an \|\| and not an && **Technical** - **Programming:** 3–5 years of professional experience in Python or another relevant language, with production-quality code standards. - **SQL:** Advanced SQL — window functions, query optimisation, schema design, and performance tuning. - **dbt:** Advanced dbt proficiency, custom macros, tests, incremental models, and multi-environment deployments (preference but not mandatory) - **Big Data:** Hands-on experience with Spark, Kafka, Presto, or Airflow in a production setting. - **Data Warehouses:** Working experience with BigQuery, Redshift, or Snowflake in a client or production context. - **IaC:** Practical experience with Terraform for infrastructure provisioning and management. - **Cloud:** Experience with cloud infrastructure and data services on AWS, GCP, or Azure. Associate-level certification or equivalent. - **Version Control:** Proficient with Git-based workflows, including branching strategies, PRs, and CI/CD integration. **Soft Skills & Language** - Ability to operate autonomously within client engagements, managing your own delivery whilst communicating progress clearly. - Critical thinking applied to architecture and solution design — you push for the right answer, not just an answer. - Strong written and spoken English and Portuguese ## Perks * * * - Holiday Entitlement - 25 days holiday plus bank holidays - Learning & Development: 1.500€ training budget + 5 training days - Company Bonus - Discretionary company and personal bonus paid quarterly - Pension Scheme - Choose Your Kit - Select from a range of laptops and accessories - Social Events: meeting - Ups, Squad events, Summer/ Christmas events, etc. - And many others.