Snowflake Data Engineer

Job Description

About Xebia

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Xebia is a trusted advisor in the modern era of digital transformation, serving hundreds of leading brands worldwide with end-to-end IT solutions. The company has experts specializing in technology consulting, software engineering, AI, digital products and platforms, data, cloud, intelligent automation, agile transformation, and industry digitization. In addition to providing high-quality digital consulting and state-of-the-art software development, Xebia has a host of standardized solutions that substantially reduce the time-to-market for businesses.

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Xebia also offers a diverse portfolio of training courses to help support forward-thinking organizations as they look to upskill and educate their workforce to capitalize on the latest digital capabilities. The company has a strong presence across 16 countries with development centers across the US, Latin America, Western Europe, Poland, the Nordics, the Middle East, and Asia Pacific.

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With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition.

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We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Functional Programming, Low Code, and Microsoft.

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We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services.

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For more details please visit

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Snowflake Data Engineer

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Location: Washington DC Work Mode: Onsite

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Job Description:

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Purpose

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Build and manage the modern cloud data platform across ingestion, transformation, and delivery layers.

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Role Summary

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This role combines Snowflake engineering, Fivetran-based ingestion, and dbt analytics engineering into one end-to-end data engineering position. The Data Engineer will modernize legacy SQL Server / SSIS / SSAS workloads into a scalable cloud platform with stronger automation, validation, lineage, and reporting readiness.

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This role leads the technical implementation of data storage, transformation, access patterns, and performance optimization in Snowflake, while ensuring the platform supports business reporting, historical analysis, governance, and future AI-enabled use cases.

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Key Responsibilities

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Design, configure, and maintain the Snowflake platform, including databases, schemas, warehouses, roles, security policies, and environment setup across development, test, and production.

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Implement and manage cloud-based ingestion using Fivetran for legacy, operational, and SaaS source systems, including full-load, incremental, and CDC-based patterns.

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Build and optimize the target data architecture across raw, staging, curated, and reporting-ready layers, aligned to medallion-style or equivalent modular design patterns.

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Develop, test, and maintain dbt models that replace legacy SSIS transformation logic and support curated business-ready data assets for reporting, reconciliation, and analytics.

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Translate legacy constructs such as SCD Type 2 handling, lookup logic, conditional branching, and other ETL patterns into modern Snowflake and dbt implementations.

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Configure AWS integrations required for the data platform, including S3 stages, IAM roles, storage integrations, encryption support, and secure connectivity patterns.

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Establish and support source-to-target mappings, metadata consistency, schema evolution handling, and documentation of field-level lineage across ingestion and transformation layers.

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Implement automated data quality checks, freshness checks, reconciliation controls, and exception handling to improve trust in the data before it reaches reporting layers.

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Monitor ingestion pipelines, connector health, transformation runs, and Snowflake workloads; troubleshoot failures, schema drift, performance issues, and data incidents.

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Optimize Snowflake cost and performance through workload isolation, warehouse sizing, clustering, query tuning, and platform monitoring.

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Support downstream analytics and reporting teams by delivering trusted, well-documented, analytics-ready data structures compatible with Sigma and other governed reporting tools.

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Contribute to CI/CD, release automation, and Git-based engineering workflows for dbt, Snowflake, and data pipeline changes.

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Produce operational documentation, configuration standards, runbooks, and handover materials for ongoing support and client operations teams.

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Work closely with architects, analysts, reporting teams, and client stakeholders to ensure the solution improves automation, reduces manual dependency, and supports a more scalable operating model.

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Required Skills and Experience

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Strong hands-on experience implementing Snowflake in enterprise environments.

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Deep knowledge of SQL, query optimization, performance tuning, and warehouse design.

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Experience migrating from legacy EDW platforms such as SQL Server, SSIS, and SSAS.

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Exp. with dbt, Fivetran, AWS, and Sigma BI/reporting integrations.

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Hands-on experience with Fivetran or comparable cloud ingestion tools.

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Strong AWS fundamentals: S3, IAM, KMS, VPC, PrivateLink for Snowflake connectivity

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Strong understanding of source-to-target mapping, CDC concepts, and incremental loading.

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Experience working with Snowflake and cloud-based data platforms.

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Ability to write SQL for data validation and reconciliation between source and Bronze landing tables

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NICE TO HAVE

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Snowflake SnowPro Core or Advanced: Data Engineer certification

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Experience with Snowflake cost optimization on large-scale financial data workloads

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Familiarity with dbt project structure and Snowflake-specific dbt materializations (dynamic tables

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