Were looking for a Data Engineer with a passion for analytics to join our growing data team! This role is ideal for someone who enjoys working across the entire data pipeline.
From data ingestion and transformation, all the way to creating analytics-ready datasets.
Youll get hands-on experience with modern tools, collaborate across functions, and help deliver data-driven insights that shape key decisions.
Youll be part of a supportive team, where mentorship, impact, and learning go hand in hand.
Responsibilities
What Youll Do:
Design, develop and maintain end-to-end data pipelines: extract raw data from sources such as MongoDB, MySQL, Neo4j, and Kafka; transform and load it into our Snowflake data warehouse.
Contribute to data modeling and data quality efforts to ensure reliable, analytics-ready datasets.
Collaborate with analytics, engineering, and business teams to understand data needs and translate requirements into actionable data solutions.
Enable data-driven decisions by building dashboards and reports using tools like dbt and AWS QuickSight.
Learn and grow in both the technical and business-facing sides of data.
Requirements: 13 years of experience in a data-related role (data engineering, analytics engineering, BI) or strong projects/coursework if you're just starting out.
Strong experience with SQL and Python for building, manipulating, and analyzing data
Comfortable with modern data tooling such us - Snowflake, dbt, Airflow, or similar
Enthusiastic about working collaboratively with teammates and stakeholders to deliver business value from data
Strong communicator and continuous learner, ready to tackle new challenges in a fast-paced environment
Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and familiarity with services like AWS Glue, Google BigQuery, or Azure Data Factory.
Hands-on experience with ETL/ELT processes, data ingestion, data transformation, data modeling, and monitoring.
Nice to Have:
Experience with AWS or other cloud platforms.
Familiarity with streaming data (Kafka), Infrastructure as Code (Terraform), or Git-based workflows
Knowledge of SaaS analytics, especially for product or customer behavior.
Understanding of PII, data privacy, or compliance standards.
This position is open to all candidates.