Data Engineer - West Region

Slalom is a business and technology consulting company that co-creates custom software, data, AI, and cloud solutions with clients. The Data Engineer will collaborate with clients, architects, and multidisciplinary teams to design, build, and operationalize scalable, governed data platforms, pipelines, and products across cloud and data ecosystems.

Responsibilities

Designing and implementing cloud-native data platforms, data lakes, lakehouses, warehouses, and data products

Building reliable batch and streaming data pipelines, integrations, and orchestration workflows

Translating business and technical requirements into maintainable engineering solutions and actionable development tasks

Developing solutions across AWS, Azure, GCP, Databricks, and Snowflake ecosystems based on client needs and your areas of expertise

Applying software engineering practices such as version control, automated testing, CI/CD, infrastructure as code, observability, documentation, and secure development

Using AI-enabled engineering approaches and tools to improve delivery speed, quality, testing, documentation, and maintainability, with appropriate human review and responsible use

Designing, building, and operationalizing governed data platforms that support analytics, AI, machine learning, Generative AI, and agentic workloads

Enabling data quality, metadata, lineage, security, privacy, governance, performance, reliability, and cost-effective operations

Participating in technical discovery, design sessions, code reviews, demonstrations, and knowledge sharing with clients and colleagues

Contributing to reusable patterns, accelerators, and engineering communities within Slalom

Preferred

Cloud, Databricks, or Snowflake certifications

Experience in consulting or in client-facing, cross-functional delivery teams

Experience with MLOps, LLMOps, vector databases, model or prompt monitoring, feature stores, semantic layers, or AI platform operations

Experience modernizing legacy data environments or migrating workloads to cloud platforms

Experience mentoring others or contributing to technical communities and reusable assets

Cloud certifications

Databricks certifications

Snowflake certifications

Consulting experience

Client-facing experience

Cross-functional delivery

MLOps experience

LLMOps experience

Vector databases experience

Model monitoring experience

Prompt monitoring experience

Feature stores experience

Semantic layers experience

AI platform operations experience

Modernizing data environments

Migrating workloads to cloud

Mentoring experience

Technical community contribution

Reusable assets contribution

Benefits

Meaningful time off and paid holidays

Parental leave

401(k) with a match

Highly subsidized health, dental, and vision coverage

Adoption and fertility assistance

Short- and long-term disability

Yearly $350 reimbursement account for any well-being-related expenses

Discounted home, auto, and pet insurance

Hybrid work arrangement

Annual discretionary bonus

Company

Business and technology consulting firm

Seattle, Washington, USA

http://www.slalom.com/

Founded in 2001

10001+ employees

Qualifications

We welcome candidates with different combinations of experience

You do not need every skill listed below to be successful in this role

We are interested in the depth of your experience, your learning mindset, and the areas where you want to grow

Hands-on experience designing, building, testing, deploying, or supporting production data engineering solutions

Experience with at least one major cloud or data platform, such as AWS, Azure, GCP, Databricks, or Snowflake. Experience across multiple platforms is valued but not required

Proficiency in programming languages such as SQL, Python, Java and or Scala

Experience with several modern data engineering capabilities, such as data modeling, ETL/ELT, distributed processing, lakehouse architectures, streaming, APIs, orchestration, or data platform modernization

Familiarity with relevant technologies, which may include Spark, Kafka, Airflow, dbt, Dagster, Azure Data Factory, BigQuery, Redshift, Synapse, Microsoft Fabric, Delta Lake, Unity Catalog, Dataplex, Dataflow, Pub/Sub, Kinesis, Kubernetes, Terraform, or comparable tools

Understanding of how high-quality, secure, governed, and observable data foundations support AI, ML, Generative AI, retrieval-augmented generation, and agentic solutions

Experience with AI-enabled or agentic engineering practices, including using AI-assisted development tools and designing data workflows or platforms that can support intelligent agents and automated decision workflows

A commitment to responsible engineering, including privacy, security, transparency, testing, monitoring, and appropriate human oversight for AI-enabled solutions

Strong problem-solving, communication, and collaboration skills, with an ability to explain technical concepts to different audiences

A curious, growth-oriented mindset and willingness to learn new platforms, tools, and delivery approaches

Hybrid/In office: We are hybrid and require that you live within a commutable distance to a Slalom location. If your team leader or client requires you to be onsite, there are expectations that you can meet those requirements

Cloud, Databricks, or Snowflake certifications

Experience in consulting or in client-facing, cross-functional delivery teams

Experience with MLOps, LLMOps, vector databases, model or prompt monitoring, feature stores, semantic layers, or AI platform operations

Experience modernizing legacy data environments or migrating workloads to cloud platforms

Experience mentoring others or contributing to technical communities and reusable assets

Required skills

Data Engineering, AWS, Microsoft Azure, Google Cloud Platform (GCP), Databricks, Snowflake, SQL, Python, Java, Scala, Data Modeling, ETL/ELT, Apache Spark, Apache Kafka, Apache Airflow, Kubernetes

Preferred skills

Cloud, Databricks, or Snowflake certifications

Experience

Mid level