AI Data Platform Engineer
New
J
JobgetherData Platform Engineering
100% remote position within the United States.Full-TimeSenior
Salary135,000 - 170,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 8+ years of experience in data engineering
- Required Skills
- Cloud ComputingKafkaSnowflakeSparkBigQueryRedshiftDatabricks
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.
Responsibilities
- 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.
- 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.
View Full Description & ApplyYou'll be redirected to the employer's site
