Lead Data Engineer
Datasage Technologies
Mountain View, United States of America
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Senior Compensation
$ 94KJob location
Mountain View, United States of America
Tech stack
Artificial Intelligence
Airflow
Amazon Web Services (AWS)
JIRA
Information Engineering
Data Governance
ETL
Data Mart
Data Warehousing
Cursor (Graphical User Interface Elements)
Python
Productivity Software
SQL Databases
Large Language Models
Spark
Generative AI
Data Layers
PySpark
GraphQL
Splunk
Data Pipelines
Amazon Web Services (AWS)
Pagerduty
Databricks
Job description
We're looking for a hands-on Data Engineer who can operate independently.
High-visibility, high-ownership role at the center of T4I's HR data platform direct exposure to AI initiatives, cross-functional stakeholders, and the chance to meaningfully reduce day-to-day operational load for the team.
What You'll Do
- Build, maintain, and troubleshoot Spark/EMR ETL pipelines feeding HR and Workforce data marts.
- Monitor and remediate Data Asset Score issues (data quality rules, governance/PII-minimization actions) to keep HR data assets compliant ahead of deadlines.
- Be the daily coordination point between US HR business stakeholders, the IDC (India) engineering team, and platform/infra teams - translating requirements, unblocking IDC, and reporting status.
- Triage and resolve Jira tickets/bugs raised against HR data mart pipelines; write clear runbooks and pipeline documentation.
- Build semantic layers and Retrieval-Augmented Generation (RAG) pipelines.
- Integrate REST and/or GraphQL APIs into data workflows.
- Operate with minimal oversight: escalating only true blockers and proactively flag risks before they become incidents. What You Bring
Requirements
8+ years in Data Engineering, with strong hands-on Spark (PySpark/Scala), SQL, and Python.
- Experience building and operating ETL/ELT pipelines on cloud platforms (AWS EMR/S3, Databricks, or equivalent); workflow orchestration (Airflow or similar).
- Comfortable owning pipeline operations end-to-end: reading dependency graphs, diagnosing failures, working with on-call /PagerDuty/Splunk, and driving fixes with multiple teams.
- Working knowledge of data warehousing/data mart design, data governance, and PII handling practices.
- AI-native mindset: familiarity with LLM capabilities, evaluation frameworks, and the creative application of AI principles to engineering challenges. Proficiency with GenAI productivity tools (e.g., Claude, Cursor, Codex) to enhance engineering workflows.
- Strong communicator; comfortable directing an offshore IDC team with minimal handholding.
Benefits & conditions
$45 an hour - Contract