Job Description

The Manager of Data Engineering is responsible for leading a team of Data Engineers in an agile development environment while driving innovation within our data warehouse and associated pipelines to meet the growing demands of our clients.


This role requires technical depth, exceptional project strategy and communication skills, and a passion for growing teams and individuals managing accessibility, privacy, quality, and availability of customer data.



We're looking for a Data Engineering Manager who thrives at the intersection of hands-on engineering, technical leadership, and team management. You will lead a team of data engineers while remaining close to the architecture and implementation of our modern data platform. This is a highly impactful role where you'll drive data strategy, enforce engineering best practices, and optimize the data ecosystem for performance, scale, and cost efficiency.

Duties and Responsibilities:

Leadership & Team Management:

+ Manage and mentor a high-performing data engineering team, fostering growth and accountability.
+ Lead hiring, onboarding, and career development for engineers.
+ Translate business needs into engineering roadmaps with clear priorities and outcomes.
+ Partner with Engineering and other development technical leads to understand roadblocks, gaps in knowledge, core competencies and opportunities to improve data access and usability.
Technical Strategy & Architecture:

+ Own the end-to-end architecture of the modern data stack--covering ingestion, transformation, storage, and analytics.
+ Set direction for scalable, modular data pipelines using tools like Airbyte, dbt, Sisense, and Snowflake.
+ Define and enforce best practices for SDLC, CI/CD, version control, and data testing within the team.
+ Partner with product, analytics, and platform teams to design future-proof data models and infrastructure.
Platform Ownership & DataOps:

+ Oversee ingestion pipelines (Airbyte/ADF), data transformation (dbt), and warehousing (Snowflake).
+ Drive DataOps maturity--automated testing, CI/CD pipelines, monitoring, and deployment workflows.
+ Ensure system observability, alerting, logging, and data quality enforcement at scale.
Infrastructure, Vendor, and Cost Optimization:

+ Lead cloud data platform operations with a focus on performance tuning, permission management cost optimization, and SLA compliance.
+ Manage vendor relationships, tool evaluations, contract renewals, and performance assessments.
+ Continuously assess and improve infrastructure reliability, resilience, and operational efficiency.

Education:

Bachelor's Degree in Computer Science, Engineering, or related technical discipline

Experience:

8+ years of experience in data engineering, with 2-4+ years in a management or technical lead capacity. Experience balancing hands-on execution with team leadership, mentoring, and cross-functional collaboration. Proven track record in coaching and mentoring data engineers Strong understanding of modern infrastructure, development tools, and software delivery practices Strong SQL skills with advanced knowledge of Joins, Unions, CTEs, Aggregations, Lag/Lead, and optimization techniques. Proficiency in Python for data manipulation, scripting, and automation. Experience working with Snowflake, dbt, and Azure Data Factory (ADF). Demonstrated experience in data modeling, including dimensional and modern approaches (Star, Snowflake, OWD). Hands-on experience in building and maintaining data pipelines (ETL/ELT). Understanding of cost optimization, caching, partitioning, and indexing strategies for performance tuning. Familiarity with BI tools such as Power BI, Sisense, Looker, Tableau, and Domo. Experience with customer personalization solutions and handling large datasets. Exposure to scripting languages like Python, Perl, or Shell.

Key Competencies:

Ownership

: Leads the team with a strong sense of accountability for data warehouse reliability, security, and performance. Defines clear expectations and processes, fosters team autonomy, and supports the development of future leaders. Acts as the escalation point for complex decisions and operational tradeoffs.

Curiosity

: Drives improvement by identifying new technologies, tools, and practices. Encourages the team to challenge assumptions and implement innovations that align with platform and business goals.

Resilience

: Provides steady leadership through incidents and change. Anticipates risks, maintains focus under pressure, and strengthens the team's ability to deliver in high-stakes or uncertain situations.

Collaboration

: Leads alignment across teams by building strong partnerships and driving shared outcomes. Communicates technical direction clearly to diverse audiences and ensures coordinated execution.

Strategic Execution

: Aligns team efforts with platform and business priorities. Manages dependencies, drives high-impact work, and builds scalable processes for consistent, high-quality delivery.

Technical Proficiency

: Applies deep infrastructure and DevOps expertise to guide technical decisions. Ensures solutions meet performance and security standards, and mentors the team to raise technical quality.

Product Knowledge

: Applies a strong understanding of Symend's platform and infrastructure needs to guide team priorities. Connects technical decisions to product performance and customer outcomes, and partners with Product and Engineering to ensure infrastructure supports product growth and differentiation.





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