Analytics Engineer, Data Platform

This is a fully remote position, open to applicants in Germany, +1 more country.

📋 Description

• Take ownership of and enhance monitoring, alerting, and observability within the data platform.

• Engage in architecture discussions, suggest improvements, document trade-offs through ADRs and RFCs, and assist in determining what to build, refactor, or decommission.

• Establish, document, and uphold engineering standards and best practices across the lakehouse, orchestration layer, data warehouse, and reporting systems.

• Foster a culture of code reviews.

• Create guides, standards, and documentation for peers within the Data domain.

• Promote alignment through knowledge-sharing forums.

• Develop and maintain internal tools, including AI-enhanced workflows and observability and quality frameworks.

• Facilitate AI adoption within data infrastructure in collaboration with the broader technology division.

• Improve and construct the Redshift data warehouse utilizing dbt and Paradime.

• Manage execution and dependencies between upstream and downstream pipelines using MWAA and Paradime.

• Provision infrastructure through Infrastructure as Code using Pulumi and Terraform.

• Contribute to ingestion pipelines using straightforward ELT, containerized Python, and event-driven patterns.

• Ensure reliable data landing into the medallion lakehouse using S3, Glue, and Iceberg.

• Collaborate across the full stack with Staff Analytics and Data Engineers to scope, develop, and deliver solutions.

• Elevate engineering standards throughout the team.

⛳️ Requirements

• Minimum of 3 years' experience in a data platform, data engineering, analytics engineering, DataOps, or a closely related role in a production setting.

• Broad understanding of the data stack and ability to switch between topics and tackle unfamiliar challenges.

• Strong proficiency in SQL and Python.

• Familiarity with databases, including query execution, performance tuning, storage, access, and permission models.

• Sufficient dbt experience to review others' contributions and establish standards.

• Practical knowledge of AWS data technologies: Redshift, S3, IAM, Athena, and Glue, or equivalent.

• Experience with lakehouse architectures such as Apache Iceberg or Delta.

• Background in pipeline orchestration tools like Apache Airflow or equivalent.

• Familiarity with modern ingestion/ELT tools such as Airbyte or Fivetran, or equivalent.

• Exposure to Infrastructure as Code, such as Pulumi or Terraform, or equivalent.

• Competence in navigating internal tools and existing codebases.

• Excellent communication and writing abilities.

• Proficient in writing documentation, guides, and architectural decisions.

• Self-starter with the initiative and autonomy to drive work independently post-onboarding.

• Fluent in English, both written and spoken.

• Located in Europe with a workable timezone overlap.

• Position requires residence in Portugal or Germany.

🏝️ Benefits

• Maturing Scale-Up: the chance to develop the next version of Emma while refining systems without sacrificing agility.

• Empowerment to Impact: ownership, accountability, and measurable development.

• Growth & Learning Journey: training and coaching based on the 70/20/10 model.

• Emma-zing Community: a collaborative community of intelligent, selective hires.

• Next Level Global: collaboration across cultures, perspectives, and time zones.

• Flexibility: a remote work policy that allows for significant flexibility.