Associate Data Engineer 2027 - AI & Data Analytics
The Associate Data Engineer at Confidential Client supports the design, development, and optimization of scalable data platforms and products that enable analytics, machine learning, and AI solutions. This role involves working with diverse data types and technologies to ensure data quality, governance, and observability, collaborating closely with clients and cross-functional teams to deliver actionable insights and AI-enabled decision-making. The position offers growth through structured learning, mentorship, and exposure to cutting-edge AI and cloud technologies within a global, innovative environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
Confidential Client is hiring an Associate Data Engineer to help design, build, and maintain data platforms and data products that support analytics, machine learning, generative AI, and agentic AI solutions. This is an entry-level / early-career role ideal for builders who enjoy turning messy data into reliable systems and working across ingestion, transformation, storage, retrieval, and observability.
- Assist in designing and implementing scalable data architectures and management systems for cloud-based analytics and AI use cases.
- Help build and optimize data pipelines, retrieval indexes, and data services for improved performance, reliability, and data freshness.
- Collect, prepare, and analyze structured, semi-structured, and unstructured data to identify trends and deliver actionable insights.
- Participate in troubleshooting data quality issues, processing failures, and retrieval gaps that affect analytics or AI systems.
- Create dashboards, reports, and observability views to communicate pipeline health and system insights to technical and non-technical stakeholders.
- Support data integrity, lineage, validation, and access control through cataloging, governance, and testing practices.
- Translate client requirements into operational data products, APIs, and tool integrations while collaborating with architects and AI engineers.
- Contribute to modern data patterns including retrieval-augmented generation (RAG), vector search, and secure interfaces for AI systems.
Required qualifications
- High School Diploma / GED required.
- Familiarity with one or more programming or query languages such as Python, SQL, Java, Scala, or JavaScript.
- Foundational understanding of data engineering concepts: data pipelines, ETL/ELT, data modeling, databases, and APIs.
- Basic exposure to cloud environments (AWS, Azure, Google Cloud, IBM Cloud, or similar).
- Ability to apply foundational statistics, ML, or information retrieval concepts to support data preparation and model-support work.
- Strong analytical thinking, problem solving, adaptability, teamwork, and communication skills.
- Willingness to travel up to 100%, based on project requirements.
- Employment type: Full-time.
- Location: Chicago, IL (on-site or client/project-based per assignment).
Preferred experience
- Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, MIS, Engineering, or related quantitative field.
- Internship, coursework, or project experience in data engineering, software engineering, cloud platforms, or analytics.
- Familiarity with tools and platforms such as Spark, Kafka, Airflow, dbt, Databricks, Snowflake, Delta Lake, or Linux.
- Experience with LLMs, embeddings, and vector databases (Pinecone, Weaviate, pgvector) and RAG pipelines.
- Exposure to orchestration / agent frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, etc.).
- Understanding of Git, containers, CI/CD, Kubernetes, observability, data governance, privacy, and security best practices.
- Relevant certifications (e.g., Google Associate Cloud Engineer, SnowProCore) are a plus.
Consulting & collaboration
- Use Agile practices to deliver production-ready data and AI solutions.
- Analyze business processes to identify opportunities for better data, automation, or tooling.
- Communicate with clarity and empathy; ask insightful questions about data meaning, risk, and business impact.
- Work cross-functionally to apply data expertise to solve complex client problems.
Why join
- Early-career development: structured learning, mentors/coaches, and opportunities to gain industry-recognized credentials.
- Hands-on experience across modern data stacks and AI-enabled solutions.
- Exposure to diverse projects and internal mobility to explore new technologies and career paths.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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