About This Role
Lead lakehouse architecture for marquee clients and the team of engineers who deliver it.
The team
Our Data Engineering practice builds the foundational platforms that feed AI, analytics, and reporting for global enterprises. Recent work includes platform transformations for global investment-analytics, food-and-facilities, and CPG clients. Engagements typically span multi-country footprints, real-time data, and tight governance requirements.
Responsibilities
- Lead end-to-end architecture of lakehouse platforms on Databricks and Snowflake, including landing-zone design, governance, and cost model.
- Design real-time streaming pipelines with Kafka, Kinesis, or Spark Structured Streaming.
- Establish data quality, lineage, and observability standards across client engagements.
- Mentor senior engineers on the team and interface directly with client CTO/CDO offices on architecture decisions.
- Own the technical relationship with the customer — design reviews, escalations, and quarterly direction.
Requirements
- 8+ years in data engineering with deep platform-architecture experience.
- Expert-level Databricks (Unity Catalog, Delta Live Tables) and/or Snowflake.
- Production experience with dbt, Airflow, and a recognized data-quality framework (Great Expectations, Soda, or similar).
- Strong SQL; Python or Scala for Spark development.
- Track record leading multi-engineer teams on enterprise engagements.
Nice to Have
- +Experience with Iceberg, Hudi, or open-table formats.
- +Background in a regulated industry (BFSI, healthcare, insurance).
- +Pre-sales or technical-account experience with Databricks or Snowflake field teams.
Required Skills
Strong SQLPython Scala for Spark development.KafkaKinesisSpark Structured Streaming
Benefits
- Competitive salary and equity
- Health, dental, and vision insurance
- 401(k) with company match
- Flexible PTO policy
- Remote work options
ACI Infotech
Enterprise technology consulting firm serving Fortune 500 clients globally.
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