Data Engineer specializing in Databricks at Sogeti implementing large - scale data processing solutions. Collaborating with Data Scientists and optimizing ETL processes for data engineering best practices.
About the role
- Enterprise Data Architect leading the design and implementation of a global data platform at Constant Contact. Collaborating cross-functionally to ensure data architecture aligns with business goals.
Responsibilities
- Help lead the design, implementation, and evolution of our global data platform
- Define the standards, blueprints, and governance models for our enterprise data architecture
- Contribute directly to development, schema design, and infrastructure optimization
- Ensure that all data-related systems, initiatives, and assets are aligned with the company's business goals, regulatory requirements, and long-term vision
- Define and roll out domain-driven data product architecture across the enterprise
- Establish standards for data contracts, schemas, SLAs, lineage, and discoverability (with DataHub)
- Develop and maintain the enterprise data architecture roadmap across AWS, Snowflake, and hybrid systems
- Design scalable solutions for real-time analytics, in-app data products, and AI/ML pipelines
- Collaborate with data governance leads to enforce policies on PII, GDPR, CCPA, and international data residency
- Work with engineering teams to enforce consistency in tools, pipelines, and naming conventions
- Provide architectural leadership across global teams and mentor engineers on best practices
Requirements
- 12+ years in data architecture, data engineering, or related fields
- At least 5+ years in an architect-level role
- Strong hands-on SQL, Python, or other data centric programming language
- Deep experience with AWS data stack (S3, Glue, Athena, Lake Formation, Kinesis/MSK, EMR/Trino, IAM)
- Experience with Snowflake, with an understanding of migration paths to AWS-native
- Knowledge of open table formats (Iceberg preferred, Delta Lake/Hudi)
- Familiarity with semantic layers (Cube.dev, dbt metrics, LookML, Superset)
- Strong understanding of data mesh principles and domain-driven data ownership
- Data governance, compliance, and security knowledge (GDPR, CCPA, SOX)
- Experience with DataHub (catalog/lineage), dbt, Tableau; Superset a plus.
- Strategic thinker who can also roll up sleeves to write SQL, debug pipelines, and build POCs
- Proven track record working across engineering, product, and data science teams in a global environment
Benefits
- Health and welfare benefits including paid leave
- Generous paid time off policy
Job title
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Degree requirement
No Education Requirement
Tech skills
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