Senior Data Engineer
Summary
Build and maintain scalable data pipelines (ETL/ELT) using Python, SQL, Spark, and Airflow to feed BI, analytics, and data science teams.
Key Responsibilities
- Design, develop, and maintain robust data pipelines (ETL/ELT).
- Build and optimize data ingestion, transformation, and delivery processes for Business Intelligence, Analytics, and Data Science teams.
- Ensure data quality, reliability, scalability, and performance across the data platform.
- Contribute to data architecture decisions and continuous platform improvements.
- Collaborate closely with technical and business stakeholders in an Agile environment.
Required Qualifications
- 5–6 years of experience in Data Engineering.
- Strong proficiency in SQL and Python.
- Hands‑on experience with data processing and orchestration tools such as Spark, Airflow, dbt, or similar technologies.
- Experience working with at least one cloud platform (AWS, Azure, or GCP).
- Solid understanding of Data Warehousing, Data Lakes, and data modeling concepts.
- Familiarity with Git and software development best practices.
Nice to Have
- Experience with Kafka or other streaming technologies.
- Knowledge of Databricks, Snowflake, or BigQuery.
- Exposure to CI/CD practices and Infrastructure as Code (IaC).
Soft Skills
- Strong analytical and problem-solving skills.
- Ability to work independently and collaboratively within cross-functional teams.
- Proactive mindset with the ability to drive technical improvements and architectural discussions.