Director, Data Engineering

Staritas• Remote, US,

17h•$165,000 - $175,000•Remote

About The Position

We are seeking an experienced Director of Data Engineering to lead our enterprise data engineering strategy, platform modernization, and operational excellence initiatives. This role will drive the design, governance, reliability, and scalability of our data ecosystem while enabling analytics, AI, and business intelligence capabilities across the organization. The Director will partner with technology and business leaders to deliver secure, trusted, and business-ready data solutions that support organizational growth and innovation.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or related field, or equivalent experience.
12+ years of progressive experience in data engineering, architecture, analytics engineering, or enterprise data platform leadership.
7+ years leading technical teams in complex enterprise environments.
Experience developing enterprise data strategies, governance programs, and modernization roadmaps.
Strong expertise with cloud data platforms, ETL/ELT frameworks, data warehousing, data integration, and production operations.
Advanced SQL skills and experience with relational and analytical databases.
Experience with AWS, Azure, Google Cloud, or hybrid cloud environments.
Experience with Informatica or similar enterprise integration platforms.

Nice To Haves

Master's degree in a related discipline.
Experience with Informatica IDMC, Databricks, Snowflake, Spark, Airflow, dbt, Azure Data Factory, AWS Glue, Power BI, and related technologies.
Experience supporting AI, machine learning, or advanced analytics initiatives.
Experience leading large-scale data modernization programs in regulated or data-driven industries.

Responsibilities

Define and execute the enterprise data engineering strategy, roadmap, and operating model.
Lead and develop high-performing teams of managers, architects, and data engineers.
Oversee the design, implementation, and optimization of enterprise data platforms, including data warehouses, lakes, lakehouses, and analytical data products.
Establish standards for data architecture, integration, governance, quality, security, observability, and DataOps.
Drive modernization initiatives that improve scalability, reduce technical debt, and enhance operational efficiency.
Enable AI, machine learning, advanced analytics, and self-service reporting through trusted data foundations.
Partner with executive leaders and cross-functional stakeholders to align data initiatives with business objectives.
Manage technology investments, vendor relationships, budgets, and resource planning.