Data Architect - West Region

Job Title:

Data Architect Who You'll Work With

Our Data Architecture & Engineering teams helps organizations modernize their data ecosystems and build the foundations required for analytics, machine learning, artificial intelligence, and Generative AI. We partner with clients to design scalable, secure, cloud-native data platforms that enable better decision-making, operational efficiency, and innovation.

Slalom maintains strategic partnerships and deep expertise across the leading cloud and data platforms, including AWS, Microsoft Azure, Google Cloud Platform (GCP), Databricks, and Snowflake. Our Data Engineering teams regularly work across multiple technologies, and we also have Centers of Excellence dedicated to each of these platforms. While expertise across all platforms is not required, your experience, interests, and strengths will help determine which team and opportunities are the best fit for you.

As a Data Architect, you will help clients design and deliver modern, scalable data platforms that enable analytics, AI, machine learning, and Generative AI solutions. Working closely with client stakeholders, engineers, and Slalom teams, you will guide architecture decisions while remaining connected to delivery and implementation.

You will:

• Design and evolve cloud-native data architectures, including data lakes, lake houses, data warehouses, and real-time data platforms.
• Translate business objectives into scalable, secure, and maintainable data solutions.
• Lead architecture and technical design efforts from discovery through implementation.
• Partner with engineering teams to deliver modern data platforms across AWS, Azure, GCP, Databricks, Snowflake, and related technologies.
• Design and operationalize AI-ready data foundations that support analytics, machine learning, Generative AI, and agentic AI workloads.
• Apply AI-enabled engineering practices to improve quality, productivity, and delivery outcomes.
• Facilitate architecture workshops, technical discovery sessions, and stakeholder alignment.
• Mentor engineers and architects, helping grow technical capabilities and foster a culture of learning and innovation.
• Collaborate with Slalom's Data Engineering teams and platform Centers of Excellence to share best practices and advance delivery excellence.
• Support business development activities, including solution design, client conversations, and technical pre-sales efforts.

You are a collaborative architect who enjoys solving complex business challenges through modern data and AI solutions. You combine strong technical expertise with the ability to communicate effectively across stakeholders, helping organizations transform data into business value.

• 8+ years of experience in data engineering, data architecture, or related technical disciplines.
• Experience designing and implementing enterprise-scale cloud data platforms and modern data architectures.
• Strong understanding of data lakes, lake houses, data warehouses, streaming architectures, and data governance concepts.
• Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and a desire to continue expanding your expertise across the broader cloud ecosystem.
• Experience leading architecture efforts from discovery through implementation while remaining engaged in delivery.
• Strong communication, consulting, and stakeholder management skills.
• Passion for mentoring others, continuous learning, and emerging technologies.

We recognize that great architects develop expertise in different technology ecosystems. We do not expect candidates to have deep experience in every platform we support.

Experience in many of the following areas is preferred:

• Cloud platforms and modern data ecosystems, including AWS, Azure, GCP, Databricks, Snowflake, and related services.
• Data engineering and analytics technologies, including distributed processing, batch and streaming architectures, data integration, orchestration, and modern data platform design.
• Development and engineering practices using technologies such as Python, Java, SQL, APIs, CI/CD, Infrastructure as Code, and containers.
• Data management disciplines including data modeling, governance, metadata, quality, security, and platform operations.
• AI, machine learning, and Generative AI solutions, including AI-enabled engineering practices, MLOps, retrieval-augmented generation (RAG), vector technologies, and agentic AI architectures.
• Designing, building, and operationalizing data platforms that support analytics, AI, ML, and Generative AI workloads at enterprise scale.

• Cloud, Databricks, Snowflake, or platform-specific certifications.
• Experience with multi-cloud environments and data platform modernization initiatives.
• Experience supporting AI transformation, data strategy, or technical pre-sales activities.