Senior Director - Data Engineering

• Role description
• Senior Director - Data Engineering

Location - Remote

Role Overview

The Director / Senior Director of Data Engineering is a dual-mandate role: you are both a hands-on technical leader and a trusted client advisor. You will work alongside our Sales and Solutions teams to win new business — crafting compelling proposals, leading discovery workshops, and shaping data engineering solutions for prospective clients — while also anchoring delivery excellence for strategic engagements. This role is ideal for someone who thrives in front of clients, speaks the language of both business and data infrastructure, and can turn ambiguous client problems into crisp, winning solution narratives.

Key Responsibilities

Pre-Sales & Solutioning

Lead technical discovery sessions and workshops with C-suite and VP-level client stakeholders to understand their data engineering challenges, priorities, and maturity

Design and articulate end-to-end data engineering solutions (architecture, platform, team model, roadmap) tailored to client context

Own the technical sections of RFP/RFI responses, proposals, and SOWs; ensure solutions are differentiated, commercially viable, and deliverable

Build and present compelling demos, PoCs, and reference architectures that accelerate deal closure

Collaborate with Account Executives and Practice leadership to qualify opportunities, shape pursuit strategies, and support pricing

Serve as a subject matter expert at industry events, client briefings, and executive roundtables

Practice & Delivery Leadership

Lead delivery governance for marquee data engineering engagements, ensuring quality, timeliness, and client satisfaction

Mentor and guide a team of data engineers and architects across projects

Define and evolve Tredence's data engineering offerings, accelerators, and point of view across modern data stack topics (cloud data platforms, lakehouse, data mesh, real-time pipelines, DataOps)

Partner with horizontal practices (Data Science, AI/ML, Analytics) to design integrated solutions

Identify and pursue expansion opportunities within existing accounts

Thought Leadership

Develop POVs, whitepapers, and solution frameworks that position Tredence as a leader in data engineering

Stay current on market trends — cloud platform roadmaps, emerging tooling, competitive landscape — and translate them into client-relevant narratives

Required Qualifications

12–18 years of overall experience in data engineering, data architecture, or data platform roles, with at least 3–5 years in a client-facing, pre-sales, or solutions consulting capacity

Demonstrated success in leading or significantly contributing to large deal pursuits ($2M+) in a services/consulting environment

Deep hands-on expertise across the modern data stack: cloud data platforms (Snowflake, Databricks, BigQuery, Redshift), orchestration (Airflow, dbt), streaming (Kafka, Spark Streaming), and cloud infrastructure (AWS, Azure, or GCP)

Strong experience designing data architectures including data Lakehouse, data mesh, data warehouse modernization, and real-time/event-driven pipelines

Proven ability to engage and influence senior client stakeholders (CTO, CDO, VP Engineering) — translating technical concepts into business outcomes

Experience owning or co-owning proposal responses, architecture blueprints, and executive presentations

Strong understanding of data governance, data quality, and DataOps practices

Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Preferred Qualifications

Experience in Retail, CPG, or Technology verticals (aligned to Tredence's core industries)

Familiarity with AI/ML platform integration and MLOps in the context of data engineering

Cloud certifications (AWS Solutions Architect, GCP Professional Data Engineer, Azure Data Engineer, Databricks or Snowflake certifications)

MBA or equivalent business acumen developed through client advisory roles

Prior experience at a top-tier analytics/data consulting firm or Big 4

What Success Looks Like in Year One

Actively contributed to 3–5 new logo or expansion pursuits, with at least 2 wins

Established as a trusted technical advisor with 2–3 strategic client accounts

Delivered at least one reusable solution accelerator or offering framework for the Data Engineering practice

Recognized internally as a go-to leader for complex solutioning and client escalations