Job Description
We are looking for a seasoned Senior Data Engineer with over 5 years of experience to design, build, and optimize our core data infrastructure. In this role, you will architect robust data pipelines, scale our data warehouse, and ensure that our data systems are highly available, reliable, and secure.
As a senior member of the team, you will collaborate closely with Data Scientists, Software Engineers, and Product Managers to turn raw data into actionable insights, while mentoring junior engineers and championing engineering best practices.
Key Responsibilities
- Architecture & Pipeline Development: Design, construct, install, and maintain highly scalable data management systems and end-to-end ELT/ETL pipelines.
- Data Warehousing & Modeling: Optimize data environments (e.g., Snowflake, BigQuery, Redshift) and design efficient data models (Star/Snowflake schemas) for complex datasets.
- Performance Tuning: Monitor, troubleshoot, and optimize data pipeline performance, ensuring low latency and cost-effective cloud resource utilization.
- Data Governance & Security: Implement data quality checks, data masking, and access controls to ensure strict compliance with security and privacy standards.
- DevOps & Automation: Integrate CI/CD practices into data engineering workflows and manage infrastructure as code (IaC) where applicable.
Required Skills & Qualifications
- Experience: 5+ years of dedicated experience in data engineering or back-end software engineering with a heavy focus on data infrastructure.
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
- Programming Languages: Expert-level proficiency in Python, SQL, and familiarity with Scala or Java.
- Big Data & Cloud Technologies: * Proven experience with cloud platforms (AWS, GCP, or Azure).
- Strong hands-on experience with modern data stack tools like Airflow, dbt, Spark, Kafka, or Flink.
- Database Expertise: Deep understanding of NoSQL databases, relational databases, and columnar storage formats (Parquet, ORC).
