As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.
Requirements:
5+ years of experience as a Data Engineer or in a similar role.
Expertise in SQL and proficiency in Python for data engineering tasks.
Proven experience designing and implementing analytics-focused data models and warehouses.
Hands-on experience with data pipelines and ETL/ELT frameworks (e.g Airflow, Luigi, AWS Glue, DBT).
Strong experience with cloud data services (e.g., AWS, GCP, Azure).
A deep passion for data and a strong analytical mindset with attention to detail.
5+ years of experience as a Data Engineer or in a similar role.
Expertise in SQL and proficiency in Python for data engineering tasks.
Proven experience designing and implementing analytics-focused data models and warehouses.
Hands-on experience with data pipelines and ETL/ELT frameworks (e.g Airflow, Luigi, AWS Glue, DBT).
Strong experience with cloud data services (e.g., AWS, GCP, Azure).
A deep passion for data and a strong analytical mindset with attention to detail.
This position is open to all candidates.
