Lead Data Engineer
New
A
Aimpoint DigitalData and AI consulting
This position is fully-remote within the US and COLFull-TimeLead
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLJavaSnowflakeDevOpsScalaData modelingdbtDatabricks
Requirements
- Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
- 5+ years working with relational databases and query languages.
- 5+ years building production data pipelines across structured, semi-structured, and unstructured data.
- 5+ years of data modeling experience, such as star schema, entity-relationship, or data vault.
- 5+ years writing clean, maintainable code in Python, Scala, Java, or similar languages.
- Experience with Databricks or Snowflake cloud data warehouses.
- DevOps experience and expertise in software engineering concepts and best practices.
- Ability to manage an individual workstream independently and lead a small team of 1–2 people.
- Experience managing stakeholders and collaborating with customers.
- Willingness to travel.
- Experience with dbt Core/Cloud, cloud ETL/ELT tools, cloud platforms, container technologies, and Apache Spark is preferred.
- Databricks or Snowflake certification is strongly preferred.
Responsibilities
- Advise client stakeholders on translating business questions into AI-ready data architectures.
- Design and implement cloud data warehouses, lakehouses, ETL/ELT pipelines, orchestration jobs, and analytical layers.
- Build semantic and analytical layers for platforms including Snowflake Cortex, Databricks Genie, BI platforms, and AI copilots.
- Engineer pipelines and data models for structured, semi-structured, and unstructured data.
- Write production-ready code in SQL, Python, and Spark, applying software engineering practices such as Git and CI/CD.
- Apply AI-assisted techniques to data exploration, quality checks, schema generation, documentation, lineage, and transformation.
- Collaborate with analytics, data science, and ML teams to productionize AI-enabled analytics, features, and inference pipelines.
- Lead small-team project delivery and contribute to internal accelerators, practice development, and business development.
View Full Description & ApplyYou'll be redirected to the employer's site
