4 часа назад
Senior Data Engineer (AI/ML)
150 000 - 200 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (AI/ML): Designing, building, and operating enterprise data lakes, warehouses, pipelines, databases, dashboards, and model-ready datasets with an accent on data platform engineering, database performance, and AI/ML data workflows. Focus on building embedding and retrieval-augmented pipelines, optimizing high-availability database environments, and delivering governed data for reporting and machine learning.
Location: Century City, Dallas, Houston, Los Angeles, New York City, Orange County, Palo Alto, San Francisco, or Washington, D.C., United States
Annual compensation: $150,000–$200,000, depending on qualifications and operational considerations.
Company
is a global law firm advising clients on significant transactions and disputes.
What you will do
- Design, build, and operate scalable enterprise data lakes, warehouses, and lakehouse environments across on-premises and cloud platforms.
- Develop and orchestrate automated ETL/ELT pipelines for structured and unstructured data, including monitoring, validation, error handling, lineage, and metadata.
- Prepare model-ready datasets and reusable data products for AI/ML training, fine-tuning, inference, feature stores, embeddings, and retrieval-augmented workflows.
- Administer relational databases, automate backups and integrity checks, troubleshoot performance issues, and manage high availability and disaster recovery.
- Develop optimized queries, semantic models, dashboards, and reports using BI tools such as Tableau or Power BI.
- Collaborate with technical and business teams, report to senior management, and mentor data engineers.
Requirements
- 10+ years of experience building and supporting enterprise data platforms, pipelines, and application databases.
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent experience.
- Proficiency with SQL and at least one data-engineering programming or scripting language, such as Python.
- Hands-on experience with data warehousing, data lakes or lakehouse architectures, ETL/ELT pipelines, and orchestration tools.
- Experience with cloud data platforms such as AWS, Azure, Google Cloud, Snowflake, or Databricks, plus distributed processing frameworks such as Apache Spark.
- Experience preparing data for AI/ML and familiarity with feature stores, vector databases, embedding/RAG pipelines, automation, and DevOps, MLOps, or CI/CD practices.
Culture & Benefits
- Health care benefits and retirement benefits.
- Paid sick time and vacation time.
- Parental leave and basic life insurance.
- Flexible Spending Accounts.
- Discretionary, performance-based bonuses.
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