Senior Data Engineer

AMI is looking for an ambitious and talented Senior Data Engineerto own the foundations of AMI’s data platform: designing and running the pipelines that bring data into our Snowflake warehouse, leading the warehouse’s clean-up and restructuring, and making sure data is accurate, documented and easy to find for the data team and for teams across AMI.

AMI’s data comes from many sources: our learning platforms, CRM, survey tools such as SurveyMonkey, programme and cohort trackers, and internal operational systems. The warehouse has grown faster than its structure. Data can be hard to find, the same metric is sometimes defined in more than one place, and too much time goes into cleaning data before it can be used. This is not an extraction-only role. You will understand the data you work with, think about how it is used downstream, and work with our software and platform engineers to improve how data is captured at source. You will be the data team’s technical voice in engineering discussions and a hands-on contributor when delivery is tight.

Key Responsibilities

Data platform and pipelines

• Design, build and maintain reliable ingestion pipelines from AMI’s source systems (learning platforms, CRM, survey tools, programme trackers and APIs) into Snowflake.

• Own pipeline orchestration, scheduling, monitoring and alerting, so failures are caught and fixed before they affect reporting.

• Manage incremental loads, schema changes and historical data so datasets stay complete and consistent over time.

• Manage warehouse performance and cost, including storage, compute usage and query optimisation.

Warehouse architecture and modelling

• Lead the clean-up and restructuring of the data warehouse: clear layers (raw, staging, modelled), naming conventions and ownership of each dataset.

• Build and maintain core data models in dbt, working with analysts so that datasets answer real business and programme questions.

• Set up and maintain a data catalogue and documentation so anyone at AMI can find what data exists, where it sits and what it means.

Data quality and governance

• Put automated data quality tests in place (completeness, freshness, uniqueness, valid values) and act on failures.

• Spot anomalies and inconsistencies in source data, trace their root cause and raise them with the relevant platform or product team.

• Apply access control, data privacy and security practices that protect participant and client data, in line with AMI policy and applicable data protection law (e.g. Kenya’s Data Protection Act).

Cross-team collaboration

• Represent the data team in technical meetings with software and platform engineers, contributing to decisions on data structures, events and integrations.

• Advise product and engineering teams on how data should be captured at source to improve quality and reduce downstream cleaning.

• Translate data requests from programme and business teams into clear technical plans with realistic timelines.

Team contribution

• Communicate proactively on progress, risks and blockers, and deliver to agreed timelines.

• Mentor analysts on SQL, modelling and engineering good practice, and set standards for code review and version control.

• Step in flexibly to support the team on priority deliverables when needed.

Requirements

Education

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Statistics, Mathematics or a related field, or equivalent practical experience.

• 6+ years in data engineering or a closely related role, including at least 2 years at senior level owning production data systems.

• Proven experience designing or restructuring a data warehouse, not only maintaining one.

• Experience integrating data from multiple operational systems through APIs, connectors and file-based sources.

• Experience working directly with software engineers on data capture, event design or application databases.

Technical skills

• Advanced SQL, including query optimisation, window functions and performance tuning.

• Strong Python for data processing, automation and API integration.

• Hands-on production experience with Snowflake or a similar cloud data warehouse (BigQuery, Redshift, Databricks).

• Strong data modelling skills (dimensional modelling, slowly changing dimensions, layered architecture) and production experience with dbt.

• Experience with orchestration and ingestion tools such as Airflow, Dagster, Prefect, Fivetran, Airbyte or Stitch.

• Version control with Git, code review and CI/CD for data projects.

• Experience with data quality and observability tools (e.g. dbt tests, Great Expectations, Elementary or Monte Carlo).

• Working knowledge of cloud platforms (AWS, GCP or Azure) and relational databases such as PostgreSQL or MySQL.

Skills & attributes

• Strong ownership: treats the warehouse as their responsibility and improves it without being asked.

• Curiosity about the data itself: what it means, where it comes from and how it is used.

• Clear, timely communication, including flagging risks and blockers early.

• Able to explain technical trade-offs to non-technical colleagues and influence engineering peers.

• Comfortable balancing planned project work with urgent operational requests.

• Relevant certifications (e.g. SnowPro Core, dbt Analytics Engineering, AWS, Azure or Google Cloud data certifications).

• Experience with survey, learning, CRM or programme/participant data (e.g. SurveyMonkey, Zoho, Netsuite, Zoom).

• Experience supporting BI and self-service tools such as Metabase.

• Experience with infrastructure-as-code (e.g. Terraform) or containerisation (Docker).

• Exposure to master data management or unique identifier design across systems.

• Experience in a learning, development-sector or impact-driven organisation, ideally across several African markets.

Benefits

Why join us

• A high-impact, diverse and ambitious team with common values:

• Be the best: We work really hard, are proud of what we do, and love delighting our clients with quality.

• Own it: We step up to the task, never pass the buck and hold ourselves accountable for delivering results.

• Push the limits: We ask why, embrace failure and try new things. We never settle.

• Do what’s right: We act with integrity, confront dishonesty, treat people fairly and strive to contribute to the greater good

• Always care: We don’t have ego - it’s always ‘team before me’. We are kind, we celebrate each other’s success, and we care enough to give honest feedback.

• A dynamic office & team life:

• Brand new offices in Westlands, Nairobi

• Monthly team social events and yearly offsite

• Regular learning and coaching opportunities

• A hybrid working model