Overview
Remote
On Site
$180000 - $205000
Full Time
Skills
Decision-making
Team Building
Roadmaps
Cloud Computing
Analytics
Data Science
Semantics
Accessibility
Mentorship
Continuous Integration
Continuous Delivery
Data Quality
DevOps
Collaboration
Data Engineering
Leadership
Databricks
Microsoft Azure
Amazon Web Services
ELT
Extract
Transform
Load
Streaming
Python
SQL
Apache Spark
Performance Tuning
Analytical Skill
Data Modeling
Snow Flake Schema
Communication
Job Details
We are building a modern, enterprise-scale data platform to support analytics, data science, and operational decision-making across a highly regulated, mission-critical domain. As our data ecosystem matures, this role exists to lead the design, build, and evolution of a cloud-based lakehouse platform and the team responsible for it.
We are seeking a Senior Manager of Data Engineering who brings strong technical judgment, hands-on architectural experience, and people leadership. You will lead a growing team building scalable data pipelines on Databricks across Azure (primary) and AWS (secondary), while establishing the standards, processes, and reliability required for long-term enterprise use.
What you will do
We are seeking a Senior Manager of Data Engineering who brings strong technical judgment, hands-on architectural experience, and people leadership. You will lead a growing team building scalable data pipelines on Databricks across Azure (primary) and AWS (secondary), while establishing the standards, processes, and reliability required for long-term enterprise use.
What you will do
- Own the data engineering architecture and technical roadmap from ingestion through consumption.
- Design and operate scalable batch and streaming pipelines using Databricks, Delta Lake, and cloud-native services.
- Lead cross-cloud data solutions across Azure and select AWS workloads.
- Partner with analytics, data science, and business teams on data modeling, semantic layers, and data accessibility.
- Build and mentor a high-performing data engineering team; set standards for code quality, CI/CD, monitoring, and observability.
- Implement governance, lineage, and data quality practices aligned with enterprise requirements.
- Drive automation and DevOps practices in collaboration with platform engineering.
- 5+ years of data engineering experience, including 2+ years in a leadership role.
- Deep hands-on experience with Databricks and Azure; AWS experience preferred.
- Strong knowledge of lakehouse architectures, ELT/ETL, and batch/streaming patterns.
- Proficiency in Python, SQL, and Spark, including performance tuning.
- Expertise in analytical data modeling (star/snowflake schemas, fact/dimension design).
- Experience building reliable, scalable pipelines for enterprise datasets.
- Strong communication skills and the ability to translate strategy into execution.
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