Senior Data Engineer
Skills
- Advanced proficiency in SQL and Python for data engineering tasks
- Experience with data processing frameworks such as Apache Spark and dbt
- Hands-on experience with cloud data warehouses (Snowflake, BigQuery, Databricks)
- Familiarity with orchestration tools (Airflow, Azure Data Factory, Prefect) and integration platforms (Fivetran)
- Experience with cloud platforms (AWS, Azure, or GCP) and building data infrastructure
- Knowledge of streaming technologies (Kafka, Spark Streaming, Flink) is desirable
- Strong communication skills for client interaction and cross-team collaboration
Responsibilities
- Lead design and implementation of scalable, low-latency data pipelines (batch and real-time) across client engagements
- Serve as technical lead and subject-matter expert for data engineering projects, resolving complex architectural and implementation challenges
- Collaborate with data solutions, analytics, and product teams to translate business requirements into technical designs
- Mentor and upskill other data engineers and embedded client teams; provide architectural guidance and code reviews
- Ensure engineering projects align with business outcomes, timelines, and quality standards
- Build and maintain cloud-based data warehouse solutions and integration with disparate data sources
- Advise on cost-efficient, performant data modeling, transformation, and storage strategies
Education
- Bachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience
- Formal training or certifications in cloud platforms or data engineering tools is a plus
Benefits
- Remote-first work environment with flexible location
- Competitive salary and comprehensive benefits package
- Professional development and mentorship opportunities
- Collaborative culture emphasizing trust, growth, and continuous improvement
- Paid time off and reasonable accommodations for disabilities
Average salary estimate
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