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data ai engineer

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div>Data &amp; AI Engineer</div><br>
<div><br>
</div><ul><li> 4-6 years of Data Engineering experience with proven hands-on experience in Big Data technologies and Business Intelligence tools.
</li></ul><ul><li> Understanding of Agile or other rapid application development methods. Exposure to design and coding across one or more platforms and languages as appropriate.
</li></ul><ul><li> Exposure to application design, software development, and automated testing methodologies.
</li></ul><ul><li> Experience with CI/CD practices using Git, Jenkins, and code integration/review processes.
</li></ul><ul><li> Backend platform: Experience building data connectors with relational &amp; nonrelational backend databases including MongoDB, PostgreSQL, and custom API Connectors.
</li></ul><ul><li> Google Cloud Platform Expertise: Hands-on experience with GCP services like BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Composer (Airflow DAGs), and Cloud Functions.
</li></ul><ul><li> Programming Languages: Strong proficiency in Python and SQL for data ingestion, processing, and manipulation.
</li></ul><ul><li> ETL/ELT: Experience with ETL/ELT processes and data warehousing concepts.
</li></ul><ul><li> Data Modeling: Understanding of data modeling principles and techniques.
</li></ul><ul><li> Cloud Technologies: Knowledge of cloud computing concepts and standard processes.
</li></ul><ul><li> AI / ML: Experience with Statistical / Predictive Modeling, Machine Learning, A/B testing, and designing feature experiments
</li></ul><div>&bull; AI Frameworks: &bull;Experience supporting AI integrations ML pipelines including BigQuery ML, or other GCP AI/ML services
</div><ul><li> BI Tools: Experience working with BI tools including Tableau and PowerBI
</li></ul><ul><li> Problem-Solving: Excellent analytical and problem-solving skills.
</li></ul><ul><li> Experience working with large datasets, ODL, identifying ingestion issues and proactively collaborating to resolve data related issues.
</li></ul><ul><li> Passion for travel/airports a plus.
</li></ul><ul><li> Experience with LLMs, Generative AI, or NLP systems.
</li></ul><ul><li> Familiarity with feature stores and model registries.
</li></ul><ul><li> Knowledge of data governance and compliance standards.
</li></ul><ul><li> Experience with real-time analytics and streaming architectures.
</li></ul><ul><li> Certifications in cloud or AI technologies.
</li></ul><ul><li> Design, build, and maintain scalable data pipelines (batch and streaming) supporting real-time / near-real-time data integration for Lounge Services Analytics use cases.
</li></ul><ul><li> Develop and optimize ETL/ELT processes for structured and unstructured data from various backend DBs and sources including MongoDB, PostgreSQL, APIs, and third-party systems.
</li></ul><ul><li> Architect and manage cloud-native data infrastructure/warehouses within Google Cloud Platform (BigQuery) environments.
</li></ul><ul><li> Orchestrate Data Transformations with Cloud Composer / Airflow DAGs.
</li></ul><ul><li> Enable trusted, analytics-ready datasets to support Tableau dashboards and analytics.
</li></ul><ul><li> Experience with observability and monitoring tools such as Datadog, CloudWatch, Prometheus, or similar platforms.
</li></ul><ul><li> Implement data monitoring, logging, and observability frameworks to ensure data quality, integrity, governance and security standards are met.
</li></ul><ul><li> Build AI / ML models and integrations to support predictive &amp; personalized use cases including lounge recommendations, capacity forecasting, and lounge optimization
</li></ul><ul><li> Collaborate with cross-functional teams including Analytics, Product &amp; Business to define data requirements and deliver solutions.
</li></ul><ul><li> Optimize data storage and processing for performance and cost-efficiency (partitioning and indexing solutions).
</li></ul><ul><li> Implement and enforce data governance standards, including data classification, access controls, and retention policies.
</li></ul><ul><li> Develop and maintain metadata management practices, including data lineage, catalog documentation, and business glossary alignment.</li></ul><br>
<div><br>
</div><div>Salary Range- $100,000-$120,000 a year
</div></div></div></div><div><div><div><b>Location</b></div>
<div>New York, NY</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Engineer</div>
</div><div><div><b>Job Id</b></div>
<div>403669</div>
</div><div><div><b>Desired Skills</b></div>
<div>Big Data</div>
</div><div><div><b>Salary Range</b></div>
<div>$100,000-$120,000 a year</div>
</div></div><p>Desired Candidate Profile
</p><div><div><b>Qualifications</b> : BACHELOR OF COMPUTER SCIENCE</div></div></div><div></div>

Data & AI Engineer

<div>
 <p>
  <strong>
   Role: Senior Data Analytics Engineer with AI Initiatives (Must)
  </strong>
 </p>
 <p>
  <strong>
   Location: New York/ Remote
  </strong>
 </p>
 <p>
  <strong>
   Experience: 5 - 10 years
  </strong>
 </p>
 <p>
  <strong>
   Duration: Full time
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Description:
  </strong>
 </p>
 <p>
  We are looking for a Lead Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI initiatives. In this role, you will work closely with data architects, analysts, and business stakeholders to develop reliable data solutions and ensure high-quality data is available across the organization.
 </p>
 <p>
  This is a
  <strong>
   hands-on engineering role
  </strong>
  focused on designing efficient data pipelines, improving data infrastructure, and enabling teams to leverage data effectively.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, build, and maintain scalable
   <strong>
    data pipelines and ETL/ELT workflows
   </strong>
   to ingest and transform data from multiple sources
  </li>
  <li>
   Develop and optimize
   <strong>
    batch and near real-time data processing pipelines
   </strong>
   for analytics and reporting
  </li>
  <li>
   Build and maintain
   <strong>
    data warehouse and data lake structures
   </strong>
   to support business intelligence and analytics use cases
  </li>
  <li>
   Implement and maintain
   <strong>
    data models
   </strong>
   that support efficient querying and reporting
  </li>
  <li>
   Improve performance and scalability of data systems through
   <strong>
    query optimization, indexing, and partitioning strategies
   </strong>
  </li>
  <li>
   Implement
   <strong>
    data quality checks, monitoring, and logging
   </strong>
   to ensure reliability of data pipelines
  </li>
  <li>
   Exposure to
   <strong>
    AI initiatives
   </strong>
   and experience
   <strong>
    building data pipelines
   </strong>
   supporting
   <strong>
    AI workflows
   </strong>
  </li>
  <li>
   Work with data architects and engineering teams to implement
   <strong>
    scalable data platform designs
   </strong>
  </li>
  <li>
   Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
  </li>
  <li>
   Maintain documentation for data pipelines, data models, and data workflows
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    5 - 10 years of experience
   </strong>
   in Data Engineering and GenAI and Data Scientist and AI Engineer
  </li>
  <li>
   Strong experience with
   <strong>
    SQL and Python
   </strong>
   for data processing and transformation
  </li>
  <li>
   Experience building and maintaining
   <strong>
    ETL/ELT pipelines
   </strong>
  </li>
  <li>
   Solid understanding of
   <strong>
    data warehousing concepts and dimensional data modeling
   </strong>
  </li>
  <li>
   Experience working with
   <strong>
    cloud data platforms or modern data infrastructure
   </strong>
  </li>
  <li>
   Familiarity with
   <strong>
    workflow orchestration tools
   </strong>
   such as
   <strong>
    Airflow
   </strong>
   or similar
  </li>
  <li>
   Understanding of
   <strong>
    API-based data ingestion and data integration patterns
   </strong>
  </li>
  <li>
   Strong problem-solving and collaboration skills
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education
  </strong>
 </p>
 <p>
  Bachelor's or master's degree in computer science
  <strong>
   , Engineering, Information Systems, or a related field
  </strong>
  , or equivalent practical experience.
 </p>
</div>


AI Data Engineer

YO IT Consulting

<div>
 <strong>
  Job Title:
 </strong>
 AI/ML Engineer
 <br/>
 <br/>
 <strong>
  Job Type:
 </strong>
 Full-Time
 <br/>
 <br/>
 <strong>
  Job Summary
  <br/>
  <br/>
 </strong>
 Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you&rsquo;ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You&rsquo;ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
  </li>
  <li>
   Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
  </li>
  <li>
   Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
  </li>
  <li>
   Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
  </li>
  <li>
   Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
  </li>
  <li>
   Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
  </li>
  <li>
   Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills And Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
  </li>
  <li>
   Hands-on experience with LLMs, RAG systems, and prompt engineering in production environments.
  </li>
  <li>
   Familiarity with multi-agent orchestration, tool use, and frameworks like LangGraph and LangChain.
  </li>
  <li>
   Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
  </li>
  <li>
   Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
  </li>
  <li>
   Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
  </li>
  <li>
   Exceptional written and verbal communication skills for effective collaboration and documentation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
  </li>
  <li>
   Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
  </li>
  <li>
   Prior exposure to government or highly regulated cloud environments and compliance standards.
  </li>
 </ul>
</div>


Machine Learning Engineer – Remote

Locality

<div><p>Locality is seeking a Senior Data Engineer whom will serve as the primary internal owner of our Audience Engine, spanning data ingestion, identity resolution, automation, and AI enablement. This role emphasizes hands on platform stewardship today, with a clear path to supporting future expansion of the HH Identity Graph and applied AI use cases.
</p><ul><li>Establish and own technical management of the Audience Engine, transitioning knowledge from external partners and building a scalable, internally managed data platform</li><li>
Reduce reliance on third-party vendors while maintaining high standards for platform reliability, uptime, and data integrity across all pipelines and integrations</li>
Architect, own, and continuously optimize Databricks Bronze Silver<li> Gold pipelines to support large scale audience ingestion, enrichment, and activation workflows</li><li>
Ensure the platform is scalable and cost efficient through effective pipeline optimization and resource management</li><li>
Proactively monitor, troubleshoot, and resolve ingestion failures, schema drift, and data quality issues across batch and near real time data pipelines</li><li>
Lead identity resolution across datasets including HHID, DSID, MAID, IP, and campaign logs, improving matching logic to strengthen the Household Identity Graph</li><li>
Guarantee accurate and timely audience publication by maintaining robust downstream data delivery processes and SLAs across activation platforms and partners</li><li>
Own and maintain integrations with external data and activation partners (e.g., Experian, FreeWheel, DSPs), ensuring seamless data exchange and operational reliability</li><li>
Partner cross functionally with Product, Analytics, and Ad Operations teams to onboard new data sources and activation endpoints, enabling new use cases and revenue opportunities</li><li>
Support and operationalize applied AI/ML workflows within Databricks, including integration with tools like Akkio, and translate business needs into production-ready data features and datasets</li><li>
Design and implement scalable data models and query-ready datasets that power BI reporting, audience insights, and predictive modeling, ensuring alignment with downstream analytics requirements</li><li>
Enforce data governance, lineage, and documentation standards while ensuring compliance with privacy, consent, and data usage regulations across all audience and identity data systems</li></ul><ul><li>
6+ years of experience as a Data Engineer or Data Platform Engineer, ideally within advertising</li><li>
Strong hands on experience with Databricks, Spark, and modern cloud data platforms</li><li>
Proven experience designing and maintaining multi-layered data architectures (Bronze / Silver / Gold)</li><li>
Deep expertise in SQL and proficiency in Python or another scripting language</li><li>
Experience working with identity graphs, audience data, and complex join logic across large datasets</li><li>
Hands on experience building and managing automated data pipelines and third-party data integrations</li><li>
Familiarity with adtech, martech, or audience activation platforms, including exposure to identity providers such as Experian or similar vendors</li><li>
Practical experience supporting AI/ML workflows or AI-enabled analytics, with an understanding of data quality, schema design, and performance optimization in cloud-scale environments</li></ul><p>
</p><p><i>Compensation for the role includes a competitive base salary in the range from $75-$100/hr (dependent on years of experience, level of education obtained, as well as applicable skillset), and an excellent benefits package (including but not limited to health care benefits, retirement benefits and paid days off).
</i></p><p></p><p><i>At Locality, we believe our biggest asset is our people. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. Locality values and solicits applications from all qualified candidates without regard to actual or perceived race, creed, color, religion, sex, gender, age, physical or mental disability, medical condition, sexual orientation, gender identity and/or expression, alienage or national origin, ancestry, citizenship status, marital status, military or veteran status, genetic information, or any other basis protected by federal, state, or local law.</i></p></div>

Sr. Data Engineer (Contract to Perm)

Realign

<div>New York, New York 10001 Posted April 2nd, 2026
 <div></div><p>Looking for more job opportunities? Click here!</p></div>
<br><div><p>Job Type: Full Time</p>
<p>Job Category: IT</p>
<p>Job Description</p>
<p></p><div><b>Job Title</b> : Software AI Engineer &ndash; Agentic AI</div><div><b>
Location</b> : New York, NY (ONSITE)<br>
<b>FTE ONLY</b></div><div></div><div><b><br>
Job Description</b></div><ul><li> 10+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure</li><li> Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.</li><li> Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.</li><li> Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.</li><li> Fluency with AI-assisted and agentic development workflows.</li><li> Comfort operating in ambiguous problem spaces and translating them into shipped, reliable autonomous systems.</li><li> Ability to influence technical direction and align teams without formal authority.</li><li> Experience in workflow engines, async processing, queues, and streaming systems.</li><li> Languages: Python, Go, TypeScript</li><li> APIs and services: REST, gRPC</li><li> Cloud and infrastructure: AWS and/or GCP, Kubernetes</li><li> Distributed systems: event-driven architectures, including Kafka</li><li> Orchestration Frameworks: LangGraph, LangChain, AirFlow, etc</li><li> Integration of commercial and open-source LLMs into agentic workflows</li><li> Agent and orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI, with strong judgment about when to use frameworks versus building lighter-weight primitives</li><li> Model-level work using PyTorch and the Hugging Face ecosystem (embeddings, fine-tuning, inference tooling), with some exposure to TensorFlow</li><li> Strong schema, validation, and state management practices using tools such as Pydantic (Python) and Zod (TypeScript)</li><li> Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.</li><li> Design, build, and operate production-grade agentic AI systems used across multiple products.</li><li> Own and evolve shared agentic AI capabilities, including:</li><li> Agent frameworks and orchestration layers</li><li> Planning, tool use, and memory strategies</li><li> Retrieval and grounding (RAG) pipelines</li><li> LLM infrastructure, inference, and model gateways</li><li> Evaluation, observability, and safety tooling for autonomous systems</li><li> Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.</li><li> Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to pro duction.</li><li> Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.</li><li> Mentor senior engineers and raise the technical bar for agentic AI development through example and influence.</li></ul><br>
<p></p>
<p>Required Skills</p>
<p>CLOUD SECURITY ENGINEER</p> <p>SENIOR EMAIL SECURITY ENGINEER</p></div>

Software AI Engineer – Agentic AI-2

Bank of America

<div>
 <strong>
  Job Description:
  <br/>
  <br/>
 </strong>
 At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
 <br/>
 <br/>
 Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates&rsquo; physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.
 <br/>
 <br/>
 Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.
 <br/>
 <br/>
 At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
 <br/>
 <br/>
 <strong>
  The Data and AI team within Global Payment Solutions (GPS) at Bank of America
 </strong>
 is looking for a highly technical Research Engineer that is a self-starter who can translate complex concepts and generate actionable insights.
 <br/>
 <br/>
 <strong>
  Who we are:
  <br/>
  <br/>
 </strong>
 The GPS Data and AI team drives and powers innovation within the one of the largest payment businesses in the world. We are the core data scientists building end-to-end production level solutions at scale. The team is a collection of individuals that welcomes challenging problems because that is where the learning begins. Many of our projects begin with &ldquo;think tank&rdquo; sessions with business teams that is later translated to tangible solutions and products.
 <br/>
 <br/>
 <strong>
  Representative Projects:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop advanced statistical methods to determine the optimal interest-rate or product pricing strategies for clients
  </li>
  <li>
   Build a Generative AI-powered search platform that enables sales and product teams to access high quality answers to product, servicing, and client related questions
  </li>
  <li>
   Develop AI models that shift foreign currency conversion &ldquo;up the payment stream,&rdquo; reducing reliability on beneficiary banks
  </li>
  <li>
   Apply advanced NLP techniques to generate near real-time insights into what clients are reaching out to servicing teams about, helping servicing teams anticipate client needs and improve service quality
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who we&rsquo;re looking for:
  <br/>
  <br/>
 </strong>
 As a Research Engineer on the GPS team, you will tackle one of our most import challenges: building models that transform data into revenue-driving insights and products. This role blends research, engineering, and product responsibilities, requiring you to design statistical models, build scalable ML pipelines, and deploy algorithms directly into our production systems. You will work across teams to solve problems in recommendation, stochastic optimization, and time-series forecasting; while running large A/B tests on new methods we design to push the boundaries of what data can achieve.
 <br/>
 <br/>
 If you are passionate about working in cross-functional teams and utilizing your skills for technical product management, statistical analytics, predictive modeling, and generating revenue, consider applying to this role.
 <br/>
 <br/>
 <strong>
  Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Frame abstract business problems using advanced data science and machine learning algorithms
  </li>
  <li>
   Work with stakeholders throughout the organization to identify opportunities for leveraging internal and external data to drive business solutions
  </li>
  <li>
   Own critical research and application development, strengthening the firm's competitive advantage
  </li>
  <li>
   Shape cross-team collaboration to advance the firm's data science capabilities
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Minimum Bachelor&rsquo;s degree in a quantitative field such as computer science, math, statistics, and physics
  </li>
  <li>
   Minimum 3 years of experience with translating mathematical models and algorithms into code (Python and/or C++)
  </li>
  <li>
   Strong foundation in probability, statistics, and applied machine learning (NLP, time-series analysis, Generative AI)
  </li>
  <li>
   Prior experience working in a highly technical data driven research environment
  </li>
  <li>
   Ability to communicate complex topics in a concise and coherent manner
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Desired Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Graduate level degree in a quantitative field such as, computer science, math, statistics, and physics
  </li>
  <li>
   Demonstrated prior experience through work, research or passion projects in RAG, Agentic Frameworks, LLMs, Reinforcement Learning
  </li>
  <li>
   Are energized by the high stakes and intensity of dynamic environments and ready to dive in whenever
  </li>
  <li>
   Are excited to dive into new technical areas on a regular basis
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Shift:
  <br/>
  <br/>
 </strong>
 1st shift (United States of America)
 <br/>
 <br/>
 <strong>
  Hours Per Week:
  <br/>
  <br/>
 </strong>
 40
</div>


Data Scientist I

Meta

<div>
 As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs, Threads). Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide.In this role, you will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions across Meta to optimize growth, strategy, and user experience for our 3 billion plus users, as well as our internal employee community.You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.Data Engineering: You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, design logging solutions, and create scalable data models. Ensuring data security and quality, and with a strong focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems.Product leadership: You will use data to shape product development, identify new opportunities, and tackle upcoming challenges. You'll ensure our products add value for users and businesses, by prioritizing projects, and driving innovative solutions to respond to challenges or opportunities.Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
 <br/>
 <br/>
 Data Engineer, Product Analytics Responsibilities:
 <br/>
 <br/>
 <ul>
  <li>
   Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
  </li>
  <li>
   Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
  </li>
  <li>
   Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
  </li>
  <li>
   Define and manage Service Level Agreements for all data sets in allocated areas of ownership
  </li>
  <li>
   Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
  </li>
  <li>
   Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
  </li>
  <li>
   Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
  </li>
  <li>
   Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
  </li>
  <li>
   Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
  </li>
  <li>
   Influence product and cross-functional teams to identify data opportunities to drive impact
  </li>
  <li>
   Mentor team members by giving/receiving actionable feedback
   <br/>
   <br/>
  </li>
 </ul>
 Minimum Qualifications:
 <br/>
 <br/>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  </li>
  <li>
   4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
  </li>
  <li>
   4+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 Preferred Qualifications:
 <br/>
 <br/>
 <ul>
  <li>
   Master's or Ph.D degree in a STEM field
  </li>
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   Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
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   Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
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   Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
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 About Meta:
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 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
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 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
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 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
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 $147,000/year to $208,000/year + bonus + equity + benefits
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 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about  benefits  at Meta.
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Data Engineer, Product Analytics

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