Manager, Software Engineering
Automox
CloudGoJavaJavaScriptMicroservicesTypeScriptVue.js
Data Engineering Manager
Angi
full-time
Posted on:
Location Type: Remote
Location: Remote • New York • 🇺🇸 United States
Visit company websiteSalary
💰 $190,000 - $210,000 per year
Job Level
SeniorLead
Tech Stack
AirflowAmazon RedshiftAWSBigQueryCloudDockerETLKafkaKubernetesPythonSparkSQLTerraform
About the role
- Lead and mentor a team of experienced data engineers, supporting their growth, performance, and technical development.
- Design and deliver large-scale, reliable, and cost-efficient data pipelines and platforms that power analytics, reporting, and data-driven products.
- Own and evolve the core compute data infrastructure built on Trino, ensuring scalable, performant, and cost-optimized query processing across the data lakehouse environment.
- Oversee major data migrations from our warehouse systems to modern, cloud-native lakehouse data platforms with minimal disruption.
- Drive the evolution of our data lakehouse and warehouse ecosystems, optimizing storage, compute, and orchestration for performance and cost efficiency.
- Collaborate closely with Product, Analytics, and Engineering teams to deliver data infrastructure that enables trustworthy and timely insights.
- Champion best practices in data modeling, governance, and observability to ensure data quality, discoverability, and reliability across the organization.
- Contribute to infrastructure and automation, leveraging tools like Terraform, Docker, Kubernetes, and CI/CD pipelines to ensure consistency, scalability, and resilience.
- Stay technically engaged, participating in architectural design, reviewing implementations, and guiding the team through complex technical decisions.
- Leverages AI tools (e.g. Copilot, Cursor, Claude Code) to improve coding speed and debug faster.
Requirements
- 8+ years of professional experience in data engineering or software engineering, with a deep understanding of distributed data systems and modern data architecture.
- 2+ years of experience managing engineering teams, including performance management and leading senior engineers.
- Proven experience building and operating large-scale, cloud-based data platforms, ideally in AWS (S3, Glue, IAM, CLI, etc.) or equivalent environments.
- Hands-on experience with SQL and Python, and a strong understanding of ETL/ELT workflows and data lifecycle management.
- Deep experience with data warehouse and data lakehouse technologies such as Snowflake, Redshift, BigQuery, and Trino as the primary compute infrastructure.
- Proficiency with workflow orchestration tools (Airflow, Dagster, Prefect, or Flyte) and data integration tools (Fivetran, Stitch, Airbyte, Meltano, or Glue).
- Experienced with infrastructure-as-code (Terraform or CloudFormation) and deployment automation.
- Comfortable with Docker and Kubernetes, deploying and scaling data-intensive workloads in containerized environments.
- Excellent communication and collaboration skills, able to work effectively across technical and business teams.
- Preferred Qualifications:
- Experience implementing or contributing to data mesh architectures.
- Familiarity with dbt and data modeling frameworks (Kimball, Star Schema).
- Experience with Spark, DuckDB, or other distributed compute frameworks.
- Exposure to event-driven architectures or streaming platforms (Kafka, Kinesis, etc.).
- Understanding of ML platforms or advanced analytics systems.
Benefits
- This position will be eligible for a competitive year end performance bonus & equity package.
- Full medical, dental, vision package to fit your needs
- Flexible vacation policy; work hard and take time when you need it
- Pet discount plans & retirement plan with company match (401K)
- The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data engineeringsoftware engineeringdistributed data systemsmodern data architectureSQLPythonETLELTdata lifecycle managementdata warehouse technologies
Soft skills
leadershipmentoringcommunicationcollaborationperformance managementtechnical decision makingbest practices advocacyproblem solvingteamworkorganizational skills
