Data Engineer

TekWissen ®; New York (NY); A distancia; USD 90.000 - 117.000; Jornada completa

Descripción de la vacante

TekWissen® Group is hiring a Data Engineer for a 12-month temporary assignment to support a major client with end-to-end data pipelines, governance and AI-enabled analytics. This remote role favors candidates in the Bay Area or nearby hubs and is open to other U.S.

locations. You will design, build and maintain scalable data architectures (Python, SQL, Spark, Airflow, PrestoDB) and ensure data quality, security and cost efficiency while collaborating with product managers and data scientists.

Formación

• 5–10 years of data engineering experience with production pipelines at petabyte scale.
• Bachelor's degree in Computer Science, Engineering or related field, or equivalent experience.
• Ability to work in a team and independently with minimal direction.
• Excellent written, presentation and verbal communication skills with stakeholder-facing reporting.
• Collaborates with data architects, modelers, Product Managers and IT team members on project goals.

Responsabilidades

• 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 scalable data management systems and production pipelines (Python, SQL, Spark, Presto).
• Design, implement, automate and maintain large-scale 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.

Conocimientos

Python

SQL

Apache Spark

Airflow

PrestoDB

Bash/shell scripting

Educación

Bachelor's degree in Computer Science, Engineering or related field

Herramientas

Scribe

Hive

Descripción del empleo

Location: Bay Area preferred, open to Seattle, New York, San Antonio, Austin

Duration: 12 Months

Job Type: Temporary Assignment

Work Type: Remote

Pay Rate: $65.00 - $85.00/HR

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.

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

Falco, Logview, Scribe, Hive ETL, Scrapy, Playwright

Move

Pub/sub and streaming

Scribe event streams, Scuba

Refine

Store & secure

Storage and access control

Hive, Manifold, XDB, TAO, Everstore, AMP, Access Gate, CAT, OIDC

Serve

Semantic layer and visualization

Orchestration

Scheduling, retries, backfills, SLAs, CI/CD

Dataswarm, Sandcastle

Configuration

Feature flags, rollouts, experiments

Observability

Monitoring, alerting, errors, on call

ODS, Scuba, ErrorTool, Oncall Hub

Development

Source control, code review, IDE

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

Knowledge retrieval, document summaries, custom commands for repetitive tasks

Agents for data collection, data quality monitoring, anomaly detection and reporting

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.