Analytics Engineer em Portugal

As the largest global micromobility business, Lime is on a mission to build a future where transportation is affordable and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership. Learn more at li. me . The Corp Tech Data & Integrations team is responsible for architecting, building, and scaling the foundational data infrastructure that powers Lime’s enterprise analytics, financial reporting, and real-time business intelligence. We are looking for an Analytics Engineer to join us in solving complex data scaling, quality, and governance challenges — partnering closely with Finance & Accounting to build systems that can withstand external audit. You will report to Lime’s Corp Tech Analytics Manager. This is a remote position with a requirement for candidates to reside in Portugal to maintain effective collaboration across teams. What You’ll Do: - Design, build, and maintain high-throughput ETL/ELT pipelines for data ingestion, processing, and storage solutions. - Develop complex, performance-tuned data transformations using Python, high-performance SQL, and tools like dbt. - Contribute to our technical strategy and how we can scale to support future business needs. - Implement data ops best practices, including CI/CD for data pipelines, version-controlled schemas (dbt), and automated testing. - Help drive data reliability and observability strategy, including improving data quality and lineage tracking. - Work with distributed processing systems like Spark, Flink, or Kafka to support scalable batch and real-time operational analytics. - Partner with the ML Platform team to prepare and provide clean, feature-rich datasets for model training and inference. - Ensure data stewardship by contributing to documentation, discoverability, and implementing robust data privacy and access controls. About You: - Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.

- 2+ years of experience in data engineering and distributed systems. - Hands-on experience building and scaling data stacks on cloud providers (AWS preferred), including experience with Snowflake. - Expertise in developing and debugging complex data transformations using Python and high-performance SQL. - Experience with workflow orchestration tools such as Airflow. - Familiarity with distributed processing technologies like Spark, Flink, or Kafka. - Understanding of data modeling, ETL pipelines, and experience with data transformation tools like dbt. - Familiarity with modern data governance tools and practices (cataloging, lineage, and PII masking). - Experience with Iceberg, Debezium, or Infrastructure-as-Code tools like Terraform for managing data infrastructure. Finance & Accounting Requirements: This role sits at the intersection of engineering and Finance. You do not need to be an accountant, but you do need to speak the language of the close and design systems that hold up under audit. - ERP fundamentals (NetSuite preferred): transactions and their GL impact, accounting periods and close calendars, dimensionality (subsidiary / department / class / location), and how upstream operational events roll into Finance reporting. - General Ledger & sub-ledgers: comfort navigating GL and sub-ledger complexity, and modeling sub-ledger-to-GL reconciliations with clear, defensible “single source of truth” definitions. - Core financial measures: consistent definition and modeling of revenue, COGS, asset balances, depreciation, accruals, and month-end close KPIs. - Fixed Assets / FAM: asset lifecycle data, depreciation logic (e. g. , straight-line), asset resets and adjustments, roll-forwards, and auditability of asset balances.