Data Engineer

Location:

Experience Level:

Employment Type:

About the Role

Senior Data Engineer Lead

balance leadership and hands-on development

Key Responsibilities

• Own delivery of data projects

  from design to deployment, ensuring timelines and quality standards are met.
• Design and implement robust

  data ingestion pipelines

  from multiple structured and unstructured sources.
• Build and optimize

  data warehouses, data lakes, and ETL/ELT pipelines

  for scalability and performance.
• Collaborate with cross-functional stakeholders to translate requirements into

  data models, pipelines, and analytics solutions

  .
• Contribute hands-on as a developer while guiding and mentoring other engineers/scientists.
• Work on

  GenAI-driven solutions

  , integrating LLMs and AI agents into data products.
• Ensure best practices for

  data governance, quality, security, and performance tuning

  .
• Drive continuous improvement in

  architecture, automation, and DevOps practices

  for data systems.

Qualifications & Skills

• 8–12 years

  of experience in

  Data Engineering / Advanced Analytics

  , with proven leadership experience.
• Strong expertise in:

• Data Engineering

  : SQL, Python, Spark, Databricks (or similar), ETL/ELT frameworks, data modeling.

• Data Warehousing & Cloud

  : Azure / AWS / GCP, Delta Lake, BigQuery, Redshift, or Snowflake.

• Data Pipelines

  : Airflow, Fivetran, Kafka, or equivalent tools.
• Exposure to

  Machine Learning / GenAI solutions

  (LLMs, embeddings, AI agents, vector databases).
• Familiarity with

  MLOps practices

  for integrating models into production pipelines.
• Strong knowledge of

  data governance, performance optimization, and cost efficiency

  in cloud environments.
• Proven ability to

  lead deliveries

  while remaining hands-on in development.
• Excellent problem-solving, communication, and stakeholder management skills.

What We Offer

• 100%

  Remote Opportunity

• Lead impactful, cutting-edge

  data and AI initiatives

  .
• Hands-on exposure to

  GenAI, LLMs, and advanced data platforms

  .
• A collaborative environment that encourages innovation and ownership.
• Career growth with leadership responsibilities while remaining technically hands-on.