Highlights
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 . 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 Professional skills and qualifications 5 10 years of data engineering experience, with production pipelines at petabyte scale.
Numbers & Facts
| Location | Los Angeles, CA (Remote) |
| Industry | Computer/IT Services |
| Salary | $65–$85 |
| Company Size | 100 to 499 employees |
| Year Founded | 2009 |
| Website | http://www.tekwissen.com/ |
Description
Overview:
Accenture helps the world's leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed for organizations across industries. With ~786,000 employees worldwide, it serves approximately 9,000 clients in 120+ countries across 40+ industries transform their operations through technology and human ingenuity. Key service lines include Cybersecurity, Digital Core, Finance, Industry and Enterprise, Song, Supply Chain and Engineering, and Talent, with advanced capabilities in AI and Data, Industry and Process, and Technology.
Job Title: Data Engineer
Location: Bay Area preferred, open to Seattle, New York, San Antonio, Austin
Duration: 12 Months
Job Type: Temporary Assignment
Work Type: Remote
Summary
Accenture helps the world's leading enterprises reinvent by building their digital core and unleashing the power of AI to create value at speed for organizations across industries. With ~786,000 employees worldwide, it serves approximately 9,000 clients in 120+ countries across 40+ industries transform their operations through technology and human ingenuity. Key service lines include Cybersecurity, Digital Core, Finance, Industry and Enterprise, Song, Supply Chain and Engineering, and Talent, with advanced capabilities in AI and Data, Industry and Process, and Technology.
Job Title: Data Engineer
Location: Bay Area preferred, open to Seattle, New York, San Antonio, Austin
Duration: 12 Months
Job Type: Temporary Assignment
Work Type: Remote
Summary
- 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.
Key responsibilities
- 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.
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 |
Professional skills and qualifications
- 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
TekWissen Group is an equal opportunity employer supporting workforce diversity.
About Company
WE THE TEKWISSEN PEOPLE
TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.
To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.
Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.
It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.
Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.Similar Job Searches
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