Principal Data Engineer
J
JobgetherHealthcare Technology
Based in United States, US Eastern or Central time zonesFull-TimePrincipal
Salary155,000 - 184,000 USD per year
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Job Details
- Experience
- 8+ years of combined software engineering and data engineering experience
- Required Skills
- PythonSQLMicrosoft Power BISnowflakeTableauAirflowData modelingdbtLooker
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.
- 8+ years of combined software engineering and data engineering experience focused on distributed data processing.
- 5+ years of experience designing, implementing, and maintaining reporting and analytics solutions (Looker, Power BI, or Tableau).
- Strong expertise in Python, SQL, database optimization, data pipelines, data modeling, governance, and security practices.
- Deep experience with cloud platforms (AWS, Azure, or GCP) and modern data warehouse technologies (Snowflake, BigQuery, or Redshift).
- Proven ability to lead large-scale data initiatives and influence architecture decisions.
- Experience designing data platforms supporting machine learning and AI workflows.
- Ability to work effectively in a fully remote environment within US Eastern or Central time zones.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong leadership, problem-solving, collaboration, and mentoring abilities.
Responsibilities
- Design and implement end-to-end data architectures, frameworks, and pipelines supporting large-scale ingestion, processing, transformation, reporting, and analytics.
- Build and optimize ETL/ELT workflows, distributed data processing systems, and data models to support business intelligence and advanced analytics.
- Develop cloud-native data solutions using technologies such as Python, SQL, dbt, AWS Glue, DMS, Airflow, Docker/Kubernetes, Snowflake, and related platforms.
- Establish engineering best practices around data quality, governance, lineage, security, privacy, performance, and reliability.
- Create and maintain monitoring, alerting, observability frameworks, and service-level objectives for critical data systems.
- Provide technical leadership, mentorship, and guidance to data engineers and engineering teams.
- Drive architectural decisions, evaluate emerging technologies, and lead complex technical problem-solving initiatives.
- Partner with software engineers, product managers, quality teams, customer success teams, and business stakeholders to define data requirements and deliver high-impact solutions.
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