Roles & Responsibilities

Proficiency in object-oriented programming with Python or Java
Experience designing and optimizing ETL/ELT pipelines
Advanced SQL skills and working knowledge of relational databases
Experience with cloud-based data warehouses such as Snowflake, Amazon Redshift, or Google BigQuery

Requirements:

Build, maintain, and scale ETL/ELT data pipelines and big data platforms powering BI and analytics
Collaborate with Data Science and Analytics teams; pair-program with engineers; work within CI/CD pipelines
Leverage AWS services and cloud data warehouses (e.g., S3, Lambda, SageMaker) and apply modular transformations (DBT)
Transform raw, structured, and semi-structured data into actionable insights and present business-oriented solutions to stakeholders

Job description

ABOUT THE OPPORTUNITY

Join a world-class technology consultancy as a Data Engineer responsible for building, maintaining, and scaling big data platforms. You'll work closely with Data Science teams to set up and automate machine learning models and algorithms for production use. This is a fantastic opportunity for someone passionate about data who's excited to use different tools to provide data insights for analysis and drive business decisions in a dynamic, collaborative environment.

PROJECT & CONTEXT

You'll build and optimize ETL/ELT data pipelines that power business intelligence and analytics initiatives across cloud-based data warehouses like Snowflake, Redshift, or BigQuery. The role involves working with raw, structured, and semi-structured data, transforming it into actionable insights for BI and Analytics teams. You'll leverage cloud services (AWS preferred) including Lambda, S3, SageMaker, and more to build scalable data solutions. Collaboration is key—you'll pair program with engineers, support analytics teams, and work within CI/CD pipelines to ensure continuous delivery. Experience with DBT (data build tool) is valuable for building modular, tested data transformations. You'll devise solutions for business problems and present them in a business-oriented manner. National and international travel varies by project (0-15% estimated).

WHAT WE'RE LOOKING FOR (Required)

Object-oriented programming: Strong proficiency in object-oriented programming languages (Python, Java, or similar)
ETL/ELT pipeline expertise: Experience building and optimizing data pipelines for ingestion, transformation, and loading
Advanced SQL knowledge: Strong working knowledge of SQL and experience with relational databases
Cloud data warehouses: Familiarity with cloud-based data warehouses such as Snowflake, Amazon Redshift, or Google BigQuery
Data handling: Experience working with raw data, structured and semi-structured data formats (JSON, Parquet, Avro)
CI/CD practices: Experience with source control (Git), Continuous Integration, Delivery, and Deployment through CI pipelines
BI and Analytics collaboration: Ability to support and work effectively with Business Intelligence and Analytics teams in dynamic environments
Pair programming: Strong collaborative skills with ability to effectively pair program with other engineers
Problem-solving: Ability to solve complex problems and present solutions in a business-oriented manner
Language requirement: Fluent English (mandatory)

NICE TO HAVE (Preferred)

Experience with DBT (data build tool) for modular data transformations
AWS cloud services experience in production (CloudFormation, API Gateway, Lambda, SSM, SNS, SQS, Firehose, S3, SageMaker)
Knowledge of Agile frameworks (Scrum, Kanban)
Experience automating Data Science models and machine learning pipelines for production
Familiarity with data orchestration tools (Airflow, Prefect)