Staff Data Engineering - Remote Eligible

Staff Data Engineering

At Axelerant, you'll architect and lead large-scale data engineering initiatives for enterprise customers, leveraging AWS and Snowflake as core platforms. This role places you at the forefront of solving complex data challenges while shaping the long-term technical direction of our clients' data ecosystems. You'll work directly with customer leadership, define future-ready architectures, and guide a high-performing engineering team to deliver modern, scalable, cloud-native data solutions.

We are looking for an experienced Staff-level Data Engineer who combines deep hands-on expertise with strong architectural thinking. You will drive technical strategy, ensure robust and secure data platforms, and enable advanced analytics and data-driven decision making. This role also involves mentoring engineers, influencing best practices, and leading the technical execution of large programs.

Your Job Responsibilities

Architecture, Strategy, and Leadership

• Design and own the end-to-end architecture of large-scale data platforms built on platforms like Snowflake and AWS.
• Define data engineering standards, patterns, and best practices for ingestion, modeling, governance, and consumption.
• Lead modernization efforts including data lakehouse design, migration planning, and platform consolidation.
• Partner with customer stakeholders to translate business requirements into scalable technical solutions.

Snowflake and AWS Expertise

• Architect optimized Snowflake environments covering data modeling, workload isolation, clustering, RLS/CLS, data sharing, and performance management.
• Implement secure, cost-efficient, cloud-native pipelines using AWS services such as S3, Athena, Redshift, Glue, Lambda, Kinesis, IAM, Step Functions, and CloudWatch.
• Leverage Snowflake capabilities including Snowpark, Streams and Tasks, Materialized Views, Data Marketplace, and Time Travel.

Pipeline Design and Optimization

• Oversee the development of high-volume batch and streaming pipelines using Spark, Kafka, Airflow, or similar technologies.
• Implement robust ETL and ELT frameworks ensuring data accuracy, lineage, observability, and governance.
• Analyze and optimize data workflows for performance, scalability, and cost efficiency.

Customer Collaboration and Technical Advisory

• Serve as the primary technical partner for customer teams, communicating architectural decisions and trade-offs.
• Lead technical workshops, discovery sessions, and solution reviews with both technical and non-technical stakeholders.
• Ensure alignment between customer goals and Axelerant's delivery approach while influencing long-term data strategy.

Team Leadership and Mentorship

• Guide and mentor a team of data engineers, fostering a collaborative, growth-oriented environment.
• Provide technical oversight across workstreams, ensuring quality, consistency, and engineering excellence.
• Facilitate knowledge sharing, code reviews, design sessions, and continuous improvement practices.

Governance, Security, and Compliance

• Establish data governance frameworks including cataloging, lineage, access controls, quality checks, and lifecycle management.
• Ensure compliance with enterprise security standards and regulatory policies across AWS and Snowflake workflows.
• Promote DataOps principles including automation, CI/CD for pipelines, testing strategies, and monitoring.

Innovation and Continuous Improvement

• Stay current with emerging tools, technologies, and patterns in data engineering and cloud architecture.
• Recommend and introduce innovative solutions to enhance customer outcomes and internal accelerators.
• Contribute to building reusable components, architectural templates, and best practice guides.

Skills, Knowledge & Expertise

Eight or more years of experience designing and delivering large-scale data solutions.

Deep expertise with Snowflake architecture including modeling, security, orchestration, and optimization.

Strong experience architecting data platforms on AWS with hands-on knowledge of core data services.

Proficiency in Python, Scala, or Java with experience building scalable data pipelines.

Strong understanding of distributed processing frameworks like Spark or Flink and streaming tools like Kafka or Kinesis.

Solid grounding in data modeling, warehouse and lakehouse design patterns, and query optimization.

Experience with orchestration tools such as Apache Airflow or Prefect.

Comfortable with containerization and orchestration using Docker and Kubernetes.

Strong understanding of data governance, privacy, and security best practices.

Excellent communication skills to work effectively with customers, engineering teams, and leadership.

Proven leadership experience mentoring teams and driving large technical initiatives.

Why Work At Axelerant?

Be part of an AI-first, remote-first digital agency that's shaping the future of customer experiences.

Collaborate with global teams and leading platform partners to solve meaningful challenges.

Enjoy a culture that supports autonomy, continuous learning, and work-life harmony.

About Axelerant

As a global company that puts care into employee happiness, engineering excellence, and customer success, we are in striking contrast to the typical outsourcing option. We are a diverse team working remotely across many time zones, with success stories that back up capabilities, and a reputation for an unconventional work environment that empowers. We are the individuals directly challenging what it means to do global delivery differently for employees and partners. Success management as our service framework operationally is part of who we are at Axelerant. All of our processes and practices are driven by this core, continuously iterated method. What this means is success management teams and success journey mapping for our partners.

Our Hiring Process

Stage 1: New

Stage 2: Interview

Stage 3: Hired

Not quite right? Register your interest to be notified of any roles that come along that meet your criteria.