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# Data Engineer

- **Company:** TekWissen LLC
- **Location:** Los Angeles, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $135,200.0 - $176,800.0
- **Contract:** Temporary contract
- **Skills:** Microsoft Access, Artificial Intelligence, Airflow, Data Analysis, Business Process Management, Capability Maturity Model Integration, Code Review, Continuous Integration, Data Discovery, Information Engineering, Data Governance, Extract Transform Load (ETL), Software Debugging, Google Talk, Monitoring of Systems, Apache Hive, Information Retrieval, Python (Programming Language), OnyX for Mac, OpenID, Microsoft SharePoint, SQL Databases, Data Logging, Scripting, Apache Spark, Phabricator, Agentic-AI, Data Layers, Information Technology, Playwright, Wikis, Data Management, Presto, Gsuite, OPUS (Software), Claude, Software Version Control, Automation Anywhere
- **Published:** November 1, 2026
- **Apply:** https://www.adzuna.com/details/5942897432

## About the Role

* 5 10 years of data engineering experience, with production pipelines at petabyte scale
 * Bachelor's degree in Computer Science, Engineering or a related field, or equivalent experience
 * Ability to work as part of a team, and independently with minimal direction
 * Excellent written, presentation and verbal communication skills, including stakeholder-facing reporting
 * Collaborates with data architects, modelers, Product Managers and IT team members on project goals
 * Strong productivity tool skills: Google Workspace, Workplace, Google Chat, Wiki, Tasks; Microsoft SharePoint a plus
 * Process certification such as Six Sigma, CBPP, BPM, ISO 20000, ITIL or CMMI

Nice to have

 * Prior experience across multiple data orgs (WhatsApp, Instagram, Reality Labs, Infrastructure, Finance Technology)
 * Track record of automating privacy and governance compliance across large dataset and pipeline estates
 * Experience building autonomous agents that triage operational tasks or access requests at scale
 * Published reusable AI workflows or agent templates for other teams
 * Platform experience: Tupperware, ThriftProxy, Relay, Buck, InternGraph Experience mentoring junior engineers and leading code review standards AI certifications, such as Anthropic Claude Certified Associate or Claude Architect Foundations

## Description

* The Data Engineer owns the data lifecycle end to end at client: from a raw log line to a trusted dashboard number. You will develop, evaluate, test and maintain data architectures and pipelines on client's internal stack, keeping data correct, timely, secure and affordable.
 * You will execute the plans, policies and practices that control, protect, deliver and enhance the value of the organization's data assets, and use client's AI assistants to work faster across every stage., * Manage data engineering projects through the full cycle, from requirements to production support
 * Identify and shape business initiatives from a data engineering perspective, working with client Product Managers and data scientists
 * Design, build, test and maintain highly scalable data management systems and production pipelines (Python, SQL, Spark, Presto)
 * Design, implement, automate and maintain large-scale enterprise ETL processes across capture, move, refine, store and serve layers
 * Orchestrate pipelines with scheduling, retries, backfills and SLAs; ship changes through code review and CI/CD
 * Ensure systems meet business requirements, client privacy policy and data governance standards, including access control and retention
 * Monitor data quality, observability, cost and reliability at every layer; participate in 24/7 on-call rotations and SEV investigations
 * Build high-performance algorithms, prototypes, predictive models and proofs of concept, including AI agents that automate operational work
 * Build datasets, semantic layers and dashboards that give stakeholders self-service access to trusted metrics

Required technical skills

 * Core languages and frameworks: Python, SQL, Apache Spark, Airflow, PrestoDB,
 * Bash/shell scripting. Candidates should have hands-on experience with the client tools below for each stage of the lifecycle.

Lifecycle stage Capability Client tools
Capture Logging, ingestion, scraping Falco, Logview, Scribe, Hive ETL, Scrapy, Playwright
Move Pub/sub and streaming Scribe event streams, Scuba
Refine Enriching, cleansing, aggregation Daiquery, Presto / Onyx, Hive, Confucius
Store & secure Storage and access control Hive, Manifold, XDB, TAO, Everstore, AMP, Access Gate, CAT, OIDC
Serve Semantic layer and visualization IData, Unidash, Vega, Nest
Orchestration Scheduling, retries, backfills, SLAs, CI/CD Dataswarm, Sandcastle
Configuration Feature flags, rollouts, experiments Configerator, Sitevars, JustKnobs, Gatekeeper
Observability Monitoring, alerting, errors, on call ODS, Scuba, ErrorTool, Oncall Hub
Development Source control, code review, IDE Sapling, Phabricator, Diffs, CodeHub, Paste, EdenFS, VS Code @ client
Investigation Entity debugging, data discovery ID Tool, IData, Intern Search
AI tooling
Candidates are expected to use AI assistants daily and to build agents that remove manual work.
Tool Expected use
Metamate Knowledge retrieval, document summaries, custom commands for repetitive tasks
Confucius Agents for data collection, data quality monitoring, anomaly detection and reporting
Claude (Opus, Sonnet) Pipeline code and code review, workflow scripting, documentation, compliance support
Analytics Agent Finding data, analysing it and answering business questions