AI Data Platform Engineer

Triwill Group; United States; On-site; USD 135,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

Remote within US

Full-time

Job summary

Jobgether is seeking an experienced AI Data Platform Engineer in the United States. This senior, architecture-focused role defines scalable architectures spanning ingestion, storage, processing, governance, and data consumption.

You’ll guide architectural direction, drive best practices, and mentor engineers while partnering with ML, BI, product, and business teams. You will shape lakehouse, warehouse, and streaming solutions using Snowflake, Databricks, BigQuery, or Redshift, and establish

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.
• 8+ years of experience in data engineering with architecture-focused roles.
• Deep expertise with two major data platforms (Snowflake, Databricks, BigQuery, or Redshift).
• Strong understanding of lakehouse architectures, table formats, distributed processing, and streaming systems.
• Production-scale experience with Spark, Flink, or Kafka.
• Experience implementing data governance, lineage, cataloging, quality, and ownership frameworks.
• Cloud platforms, IAM, security, and cost-optimization knowledge.
• Proven track record leading complex cross-functional data-platform initiatives.
• Strong communication and stakeholder-management skills.

Responsibilities

• Define target-state architecture for enterprise data platform across ingestion, storage, processing, governance, and consumption.
• Establish standards for data modeling, schema evolution, and data lifecycle management.
• Architect lakehouse, warehouse, and streaming solutions (Snowflake, Databricks, BigQuery, Redshift, etc.).
• Design end-to-end batch and streaming data pipelines balancing performance and cost.
• Lead data governance, lineage, cataloging, and discovery initiatives.
• Define security architectures including IAM, encryption, and masking.
• Partner with ML, BI, product, analytics, and business teams to meet data needs.
• Mentor engineers and architects; drive architectural best practices.

Skills

Data engineering

Architectural leadership

Cloud platforms

Governance & security

Communication & stakeholder mgmt

Education

Bachelor’s or Master’s degree in CS/IS

Tools

Snowflake

Databricks

BigQuery

Redshift

Spark

Flink

Kafka

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for anAI Data Platform Engineer based in the United States.

This is a senior, architecture-focused opportunity to shape the foundation of a modern enterprise data ecosystem. You will define scalable architectures spanning ingestion, storage, processing, governance, and data consumption. The role combines hands-on technical depth with strategic decision-making across complex data environments. You’ll work closely with data engineering, analytics, ML, product, and business stakeholders to turn platform capabilities into measurable value. You will establish standards for data modeling, security, reliability, governance, and lifecycle management. The position offers the opportunity to influence major platform initiatives while mentoring engineers and guiding architectural direction. This is a fully remote role designed for an experienced data professional comfortable leading cross-functional programs.

Accountabilities

• Define the target-state architecture for an enterprise data platform across ingestion, storage, processing, governance, and consumption layers.
• Establish technical standards for data modeling, schema evolution, partitioning, file formats, storage organization, and data lifecycle management.
• Architect modern lakehouse, warehouse, and streaming solutions using technologies such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
• Design end-to-end batch and streaming data pipelines that balance performance, latency, reliability, cost, and maintainability.
• Lead the integration of data governance, lineage, cataloging, and discovery capabilities using platforms such as Collibra, Alation, Atlan, Unity Catalog, or DataHub.
• Define security architectures covering identity-aware access, encryption, masking, and row- and column-level controls.
• Partner with ML, BI, product, analytics, and business teams to ensure the platform meets downstream data consumption requirements.
• Establish data contract and data product principles that promote clear ownership, quality, scalability, and effective separation between producers and consumers.
• Lead architecture reviews, evaluate proposed designs, and provide technical guidance to engineering and architecture teams.
• Drive data-platform cost optimization, capacity planning, high availability, disaster recovery, and multi-region strategies for critical assets.
• Mentor data engineers and architects while promoting modern platform standards, architectural consistency, and emerging best practices.
• Produce architecture documentation, including context diagrams, architecture decision records, reference architectures, and reusable design patterns.
• Monitor developments across data-platform technologies, vendors, research, and open-source ecosystems to inform future architectural decisions.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related discipline.
• 8+ years of experience in data engineering, including substantial experience in data architecture or platform architecture roles.
• Deep expertise with at least two major data platforms, such as Snowflake, Databricks, BigQuery, or Redshift.
• Strong understanding of modern lakehouse architectures, table formats, distributed data processing, and streaming systems.
• Production-scale experience with technologies such as Spark, Flink, or Kafka.
• Strong data modeling capabilities across dimensional, normalized, and data-vault approaches.
• Demonstrated experience implementing data governance, lineage, cataloging, quality, and ownership frameworks.
• Solid knowledge of cloud platforms, networking, identity and access management, security, and data-platform cost optimization.
• Proven track record of leading complex, cross-functional data-platform initiatives from architecture through implementation.
• Strong communication, facilitation, presentation, and stakeholder-management skills, with the ability to translate complex technical concepts for both technical and business audiences.
• Experience with data mesh or data product architectures is preferred.
• Familiarity with semantic-layer technologies such as dbt Semantic Layer, Cube, or LookML is advantageous.
• Experience working in regulated environments involving data residency, compliance, or audit requirements is a plus.
• Cloud or platform certifications across Snowflake, Databricks, AWS, Azure, or GCP are advantageous.
• Public speaking, technical writing, or contributions to the data architecture community are a plus.

Benefits

• Competitive salary: $135,000–$170,000 annually.
• Remote flexibility: 100% remote position within the United States.
• Employment type: Full-time, direct W-2 position.
• Career growth: Opportunity to shape enterprise-scale data architecture and influence major technology initiatives.
• Technical impact: Work across modern cloud data platforms, lakehouse architectures, streaming technologies, governance, and data products.
• Leadership opportunities: Mentor engineers and architects while establishing technical standards and architectural best practices.
• Collaborative environment: Partner with engineering, analytics, ML, product, and business stakeholders across the organization.
• Innovation-focused work: Stay at the forefront of evolving data-platform technologies, cloud services, and open-source developments.