Senior Data Engineer

Alter Domus • Salt Lake City, UT

1d • Hybrid

About The Position

Join our dynamic and innovative team as a Senior Data Engineer, where you will collaborate on the design, architecture, and optimization of our enterprise data infrastructure and pipelines. As a senior member of the team, you will provide technical leadership and mentorship while working closely with business stakeholders and the rest of the data team to ensure data is reliable, efficient, secure, and accessible at scale. You will drive best business practices, influence architectural decisions, and play a key role in shaping our data engineering strategy.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience as a Data Engineer or in a similar role working with cloud-based data platforms.
• Demonstrated experience in technical leadership, including mentoring engineers and leading architectural initiatives.
• Proven track record of delivering complex, large-scale data engineering projects.
• Expert-level proficiency with Airflow (self-managed or managed services like Amazon MWAA) for workflow orchestration, DAG development, and scheduling.
• Deep understanding of Airflow best practices including DAG structure, dependency management, error handling, scaling, and optimization.
• Advanced hands-on experience with AWS Lake Formation, S3, Athena, and related services (e.g., Lambda, Glue, IAM, CloudWatch, Step Functions).
• Experience with AWS infrastructure as code (Terraform, CloudFormation).
• Expert-level proficiency in designing and implementing data warehouses, configuring enterprise security, optimizing complex queries, and managing Snowflake at scale.
• Advanced experience with Databricks for large-scale data processing, analytics, and real-time data insights.
• Familiarity with Spark optimization and performance tuning.
• Deep expertise with Airbyte or similar tools for complex data ingestion scenarios.
• Advanced proficiency with dbt or other SQL-based transformation frameworks for modular, maintainable data processing.
• Experience with real-time streaming technologies (e.g., Kafka, Kinesis) is a plus.
• Expert-level proficiency in Python and/or Java/Scala for building robust data pipelines and custom integrations.
• Strong software engineering fundamentals including testing, documentation, and code quality.
• Expert-level knowledge of SQL for complex data manipulation, analysis, and performance optimization.
• Strong experience with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code (Terraform, CloudFormation).
• Deep understanding of DevOps best practices for managing Airflow environments (e.g., version control for DAGs, automated testing, monitoring, deployment strategies).
• Exceptional problem-solving and analytical abilities with a track record of solving complex technical challenges.
• Outstanding communication and collaboration skills, with the ability to lead cross-functional teams and influence stakeholders at all levels.
• Proven leadership and mentorship capabilities, with experience coaching and developing engineering talent.
• Ability to operate effectively in a fast-paced, agile environment and manage multiple strategic priorities simultaneously.
• Strong business acumen and ability to align technical solutions with business objectives.

Nice To Haves

• AWS certifications (e.g., AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect) are a plus.
• Snowflake certifications (e.g., SnowPro Core) are a plus.
• Databricks certifications are beneficial.
• Demonstrated Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code (Terraform, CloudFormation).
• Strong foundation in DevOps best practices for managing production data environments.
• While familiarity with financial services data especially private equity and alternative investments is not necessary, it will be highly impactful for this role.

Responsibilities

• Data Pipeline Orchestration
• Design, architect, and maintain complex end-to-end data pipelines using Airflow (including managed services like Amazon MWAA) to orchestrate, schedule, and monitor batch/streaming workflows at enterprise scale.
• Develop and optimize sophisticated DAGs (Directed Acyclic Graphs) with advanced retry logic, error handling, alerting, and monitoring to ensure maximum data quality and pipeline reliability.
• Establish best practices and standards for pipeline development, testing, and deployment across the organization.
• Data Ingestion & Transformation
• Architect and implement scalable data integration solutions using Airbyte for ingestion and dbt for transformations in a modular, maintainable fashion.
• Collaborate with Data Analysts and Data Scientists to design and implement complex transformations and business logic, ensuring data is analytics-ready and optimized for performance.
• Mentor junior engineers on data ingestion patterns and transformation best practices.
• Data Modeling & Warehousing
• Design and implement sophisticated data models and architectures for both structured and semi-structured data across AWS S3 (data lake) and Snowflake (data warehouse).
• Databricks implementations for advanced data processing, analytics, and real-time insights capabilities.
• Ensure data schemas and transformations support advanced analytics, BI reporting, machine learning use cases, and emerging business needs.
• Drive data architecture decisions and provide technical guidance on data modeling strategies.
• Data Governance & Security
• Lead implementation of AWS Lake Formation APIs and enterprise-level best practices to maintain data security, access controls, and regulatory compliance.
• Partner with IT security and compliance teams to establish and enforce robust encryption standards, comprehensive audit trails, and identity/role-based access controls.
• Champion data governance initiatives and establish data quality frameworks across the organization.
• Performance Optimization & Cost Management
• Lead optimization efforts for AWS Athena queries and configurations (e.g., data partitioning, indexing strategies) for superior performance and cost efficiency.
• Monitor, analyze, and tune Airflow DAGs, Snowflake queries, and Databricks jobs to maximize throughput, reliability, and cost-effectiveness.
• Implement monitoring and alerting solutions to proactively identify and resolve performance bottlenecks.
• Technical Leadership & Stakeholder Management
• Provide technical leadership and mentorship to junior and mid-level data engineers, fostering a culture of continuous learning and excellence.
• Lead cross-functional partnerships with DevOps, Platform Engineering, Data Science, and business teams to ensure seamless integration of data workflows and systems.
• Communicate complex technical solutions effectively to non-technical stakeholders and executive leadership, translating business requirements into scalable technical solutions.
• Drive architectural decisions and represent the data engineering team in strategic planning discussions.
• Strategic Planning & Continuous Improvement
• Lead architecture reviews, design reviews, and code reviews to ensure quality, scalability, and alignment with enterprise best practices.
• Drive innovation by evaluating and recommending emerging trends and technologies in data engineering, orchestration tools (Airflow, MWAA), and cloud services (AWS, Snowflake, Databricks).
• Contribute to the development of the data engineering roadmap and long-term technical strategy.
• Champion DevOps and DataOps best practices, including CI/CD for data pipelines, infrastructure as code, and automated testing.

Benefits

• Support for professional accreditations
• Flexible arrangements, generous holidays, plus an additional day off for your birthday!
• Continuous mentoring along your career progression
• Active sports, events and social committees across our offices
• 24/7 support available from our Employee Assistance Program
• The opportunity to invest in our growth and success through our Employee Share Plan
• Plus additional local benefits depending on your location

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level