01Overview
Job Description:
Role Overview
This role combines Data Engineering leadership with enterprise transformation ownership. You will lead a distributed data engineering and automation team while personally driving architecture, modernization, and high-impact delivery. You are accountable for turning legacy-heavy, labor-intensive systems into modern, automated, cloud-native platforms that measurably reduce cost, risk, and friction across the business.
This is not a pure people-management role and not a strategy-only role. You will design, code, refactor, automate, govern, and communicate. You'll coordinate across business, finance, and technology, translating executive goals into scalable data and automation solutions that actually ship.
If you enjoy owning outcomes end-to-end, modernizing messy environments, and leading from the frontthis role fits.
Key Responsibilities
Leadership, Strategy & Delivery
Lead, mentor, and develop a high-performing, remote data engineering and transformation team across multiple time zones.
Set clear priorities, execution plans, and accountability for data, automation, and transformation initiatives.
Own hiring, performance management, coaching, and career development.
Build a culture of ownership, proactive problem-solving, and delivery over theater.
Data Architecture & Platform Modernization
Own the data architecture and automation roadmap, driving the transition from legacy systems to modern, scalable, cloud-native platforms.
Design and implement data models, pipelines, integrations, and automation frameworks aligned with business and financial priorities.
Lead large-scale refactoring and modernization initiatives to eliminate technical debt and improve reliability, performance, and transparency.
Ensure cross-system compatibility through enterprise architecture principles and governance.
Automation & Transformation Portfolio Ownership
Own the end-to-end automation and transformation portfolio across data, workflows, integrations, and RPA.
Define automation strategy, governance models, standards, and success KPIs tied to efficiency, cost reduction, and control improvement.
Ensure alignment between automation initiatives and accounting, finance, shared-services, and operational workflows.
Identify opportunities to replace manual, error-prone processes with durable, automated solutions.
Hands-On Engineering & Execution
Actively write and review codedata pipelines, transformations, automation logic, orchestration, and internal tooling.
Build and optimize SQL, Python/Scala services, ELT pipelines, and workflow orchestration.
Rapidly prototype solutions to validate ideas and accelerate decision-making.
Conduct code reviews, enforce quality standards, and ensure platform stability, security, and observability.
Best Practices, Governance & Enablement
Establish and enforce standards for:
Modular data design
CI/CD for data and automation
Observability, DataOps, and platform reliability
Governance, lineage, controls, and auditability
Actively teach and uplift the teammodern tools, patterns, and architectural thinking.
Reduce operational friction through automation, standardization, and platform reuse.
Stakeholder & Executive Engagement
Serve as the primary bridge between technology, business, finance, and executive leadership.
Lead communication with senior leadership and oversight committeesclear, factual, outcome-driven.
Present strategy, progress, risks, and ROI in language executives understand.
Manage vendors, contracts, and budgets with a focus on measurable value and cost control.
Required Qualifications
10+ years in data engineering, enterprise technology, or automation leadership.
5+ years leading team of 10-20 people and major initiatives in complex, multi-system environments.
Proven success leading distributed, remote teams across time zones.
Deep hands-on expertise with:
SQL (expert-level)
Python and/or Scala
ELT/ETL frameworks (dbt, Airflow, Dagster, etc.)
Azure Data Factory
Snowflake
Cloud platforms (Azure, AWS, or GCP)
Orchestration, CI/CD, automation, and containerized workloads
Demonstrated success modernizing legacy platforms and eliminating significant technical debt.
Strong understanding of automation platforms (RPA, workflow orchestration, integration tooling).
Experience aligning technology initiatives with financial operations, controls, and efficiency goals.
Excellent communicator able to simplify complex systems for executives without dumbing them down.
Preferred Qualifications
Background in Financial Services, Accounting Outsourcing, SaaS, or BPO environments.
Familiarity with accounting workflows, shared-services models, and compliance controls.
Experience building internal platforms or self-service data and automation tooling.
Solid .
