Lead Data Engineer

Posted 16 days agoViewed

💎 Seniority level: Lead, 7+ years

📍 Location: United States

💸 Salary: 175000.0 - 215000.0 USD per year

🔍 Industry: Mental Health Care

🏢 Company: Charlie Health👥 501-1000💰 $850,000 Seed over 4 years agoMental Health Care

⏳ Experience: 7+ years

🪄 Skills: PythonSQLNumpySnowflakePandas

Bachelor’s degree in Computer Science, Mathematics, or other technical discipline, or equivalent practical experience.
7+ years experience as a software engineer, with at least 5 years of experience in a data engineering role.
Deep expertise in SQL, understanding CTEs, aggregation functions, window functions, partitioning, and clustering.
High proficiency in Python and experience with common data engineering libraries such as Pandas, Numpy, and Great Expectations.
Experience with a modern data stack and tools such as FiveTran, Snowflake, DBT, Dagster, Hightouch, and Tableau.
Experience with data exploration, profiling, governance, visualization, and activation.
Proven ability to thrive in an ambiguous and rapidly changing environment.
Experience working with sensitive data in a regulated environment.
Expertise in healthcare is a plus.

Develop, release, and maintain high-quality data pipelines using Python, FiveTran, DBT, and Snowflake.
Own and guide the development of the data infrastructure.
Develop custom integrations using Dagster.
Configure reverse ETL integrations using Hightouch.
Identify bottlenecks and implement improvements to data engineering processes, tools, and procedures.
Promote collaboration and learning across teams through mentoring and knowledge sharing.
Participate in on-call rotation to ensure data availability.

Posted about 1 month ago

📍 United States of America

🧭 Full-Time

💸 140000.0 - 170000.0 USD per year

🔍 Insurance

🏢 Company: joinroot

4+ years as a software engineer.
2+ years leading software teams.
Expertise in Python, Terraform, SQL, and Spark.
Expertise in Cloud Architecture.
Experience with telematics or sensor data collection systems.
Proven leadership of projects across multiple teams and functional domains.
Excellent communication skills with engineering colleagues and senior business leaders.

Partner with Marketing, Product, Data Science, Analytics, and Insurance experts to set the strategy for the quarters to come.
Identify and socialize important technical initiatives that increase the effectiveness of products, systems, and teams.
Coach and guide engineers in planning experiments and projects aligned with strategic objectives.
Contribute code each development cycle to advance the team’s impact.
Lead incident response to improve system resiliency.
Coordinate with Staff Engineers to establish and evangelize standards and best practices.

LeadershipPythonSQLStrategyData scienceSparkCommunication SkillsCollaborationTerraform

Posted about 1 month ago

Posted 3 months ago

📍 United States

🔍 Data Management

Bachelor's degree or higher in Computer Science, Data Engineering, or related fields. Equivalent work experience is also highly valued.
5-10 years of experience in data engineering, software engineering, or client deployment roles, with at least 3 years in a leadership capacity.
Strong leadership skills, including the ability to mentor and motivate a team, lead through change, and drive outcomes.
Expertise in designing, building, and optimizing ETL/ELT data pipelines using Python, JavaScript, Golang, Scala, or similar languages.
Experience in managing large-scale data processing environments, including Databricks and Spark.
Proven experience with Apache Airflow to orchestrate data pipelines and manage workflow automation.
Deep knowledge of cloud services, particularly AWS (EC2/ECS, Lambda, S3), and their role in data engineering.
Hands-on experience with both SQL and NoSQL databases, with a deep understanding of data modeling and architecture.
Strong ability to collaborate with clients and cross-functional teams, delivering technical solutions that meet business needs.
Proven experience in unit testing, integration testing, and engineering best practices to ensure high-quality code.
Familiarity with agile project management tools (JIRA, Confluence, etc.) and methodologies.
Experience with data visualization and analytics tools such as Jupyter Lab, Metabase, Tableau.
Strong communicator and problem solver, comfortable working in distributed teams.

Lead the configuration, deployment, and maintenance of data solutions on the Demyst platform to support client use cases.
Supervise and mentor the local and distributed data engineering team, ensuring best practices in data architecture, pipeline development, and deployment.
Recruit, train, and evaluate technical talent, fostering a high-performing, collaborative team culture.
Contribute hands-on to coding, code reviews, and technical decision-making, ensuring scalability and performance.
Design, build, and optimize data pipelines, leveraging tools like Apache Airflow to automate workflows and manage large datasets effectively.
Work closely with clients to advise on data engineering best practices, including data cleansing, transformation, and storage strategies.
Implement solutions for data ingestion from various sources, ensuring the consistency, accuracy, and availability of data.
Lead critical client projects, managing engineering resources, project timelines, and client engagement.
Provide technical guidance and support for complex enterprise data integrations with third-party systems (e.g., AI platforms, data providers, decision engines).
Ensure compliance with data governance and security protocols when handling sensitive client data.
Develop and maintain documentation for solutions and business processes related to data engineering workflows.
Other duties as required.

AWSLeadershipProject ManagementPythonSQLAgileApache AirflowETLJavascriptJiraTableauStrategyAirflowData engineeringGoNosqlSpark

Posted 3 months ago

🔧 Requirements