Data Engineer

Role Overview

We are seeking a seasoned Data Engineer to join our Engineering team. You will design, build, and operate the data platform that powers analytics, research, and product decisions across the organization. This is a hands-on role for someone who is equally comfortable modeling complex datasets, engineering resilient pipelines, and managing the underlying cloud infrastructure. You will own systems from ingestion and transformation through to the warehouse layer, and you will set the standards that keep our data trustworthy. Beyond building, you will partner closely with analytics, product, and platform teams to define how data moves through the organization and to raise the bar for reliability, quality, and governance.

Key Responsibilities

Data Modelling & Transformation

• Model and structure data for analytical and operational use, owning the transformation layer and its tooling, including dbt
• Design data models that are clear, well documented, and easy for downstream teams to build on
• Define and enforce data contracts and schema standards in collaboration with upstream and downstream engineering teams

Pipelines & Orchestration

• Design and build scalable batch and streaming data pipelines across ETL, ELT, and change data capture patterns
• Orchestrate and schedule workflows using tools such as Airflow, Dagster, or Prefect
• Ensure pipelines are observable, recoverable, and well instrumented, with monitoring and data quality checks that catch issues before they reach consumers

Data Warehousing & Infrastructure

• Architect and optimize our modern data warehouse, including storage layer design, table formats, and compute and query engine integration
• Provision and maintain cloud infrastructure using infrastructure as code, and manage deployment and container orchestration
• Implement privacy, anonymization, and governance controls to keep sensitive data protected and compliant

Collaboration & Communication

• Participate in planning and requirements discussions to raise data quality and modeling concerns before development starts
• Translate requirements from analysts, researchers, and product engineers into robust data models and reliable delivery
• Keep engineering and the wider organization connected through transparent, timely communication

Qualifications

• Advanced SQL, including performance tuning and complex analytical query design
• Advanced Python for pipeline development, tooling, and automation
• Familiarity and hands-on experience with AWS, Azure, GCP, AliCloud, or an equivalent
• Data warehousing: expert knowledge of one modern platform (Snowflake, BigQuery, Databricks, or Redshift), including architecture, storage layer design, table formats, and compute and query engine integration
• Experience developing and orchestrating data pipelines across ETL, ELT, CDC, and stream processing
• Data modeling and tooling expertise, including dbt
• Experience with modern orchestration tools like Airflow, Dagster, or Prefect
• Working knowledge of cloud infrastructure tooling, including Terraform, Helm, and Kubernetes or equivalent
• Experience defining and enforcing data contracts or schema standards in collaborative engineering environments
• Exposure to privacy and anonymization implementations
• Background in a SaaS, startup, or product-led environment is a plus
• Familiarity with data observability and lineage tooling such as Sentry or Datadog is a plus

Assignment

• Technical assessment assigned after candidate screening.

Yaqeen Institute embraces a philosophy that values and promotes diversity. Our goal is to attract, develop, retain, and advance a talented and diverse workforce within a culture where all employees are empowered to reach their fullest potential.

Please note that all career opportunities at Yaqeen Institute are subject to a three-month probationary period, during which we assess performance, alignment with our values, and mutual fit to ensure long-term success in the role.