Data Engineer II - Confluent

At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world.

About the Role

As a Data Engineer II on the Data team, you will own meaningful slices of our data platform end-to-end — from ingestion through transformation to the data products that power decision-making across the company. You'll design and operate batch and real-time pipelines, partner closely with Data Scientists, Analysts, and business stakeholders, and raise the bar on craftsmanship, reliability, and developer productivity for the team.

You'll work in a modern, AI-augmented engineering environment: shipping faster with Claude Code and other AI coding assistants, building AI-powered internal tools (natural-language-to-SQL, automated data quality, lineage, anomaly detection), and bringing GenAI thoughtfully into data workflows. We expect you to take significant projects from ambiguous problem statement to delivered outcome, mentor newer engineers, and represent the team confidently with cross-functional partners.

What You Will Do

• Design, build, and operate efficient, reliable, and well-documented data pipelines across batch and streaming systems — from source ingestion through the warehouse to consumer-facing data products.

• Own the data models, SLAs, and quality contracts for the domains you cover; treat documentation, testing, and observability as first-class deliverables.

• Improve the data platform itself: introduce or extend tooling, templates, CI/CD, testing frameworks, and monitoring that make the entire team faster and more reliable.

• Adopt and champion AI-assisted engineering — use Claude Code and similar tools as part of your daily workflow, build internal AI-powered utilities (text-to-SQL on the semantic layer, automated PR review, log triage, data discovery), and evaluate where LLMs add durable value vs. hype.

• Partner directly with Data Scientists, Analysts, and business stakeholders to translate ambiguous requirements into well-scoped deliverables; communicate trade-offs, anticipate push-back, and drive alignment without needing escalation.

• Mentor interns, new hires, and L2 engineers — through onboarding, code review, design feedback, and pairing.

• Contribute to cloud infrastructure and governance: IAM, service accounts, secrets management, cost optimization, and Terraform-managed GCP / Confluent Cloud resources.

• Drive incident response and root-cause analysis for the pipelines you own; close the loop with durable fixes, runbooks, and prevention.

• 4 to 7 years of experience in Data Engineering at a technology company, including production ownership of non-trivial pipelines and data models.

• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.

• Strong command of advanced SQL and Python — you can write production-grade code, review others' code, and pick the right tool for the job.

• - Solid grounding in dimensional modeling, data warehousing, and ELT/ETL fundamentals; you can design a clean star schema and explain the trade-offs.

• - Hands-on experience operating orchestration frameworks in production (Airflow / Cloud Composer, Dagster, or similar).

• - Hands-on experience building streaming and event-driven pipelines — Kafka, Flink, or equivalent — and reasoning about exactly-once, schema evolution, and back-pressure.

• - Experience on a major cloud platform (GCP preferred) and with infrastructure-as-code (Terraform).

• - Demonstrated ability to operate with moderate ambiguity: scope your own work, identify what to clarify, recommend an approach, get buy-in, and ship.

• - Fluency with AI coding assistants (Claude Code, Cursor, Copilot) as a daily tool — and judgment about where they help vs. where they hurt.

• - Clear written and verbal communication; comfortable presenting designs, post-mortems, and trade-offs to technical and non-technical audiences.

- Production experience with dbt (or SQLMesh) and the surrounding ecosystem — testing, packages, semantic layers (dbt Semantic Layer, Cube, Hex).

- Experience with open table formats (Apache Iceberg, Delta Lake) and modern lakehouse patterns.

- Familiarity with data quality / observability tooling (Great Expectations, Soda, Elementary, Monte Carlo) and catalog / lineage systems (DataHub, Atlan, Unity Catalog).

- Experience building or integrating with AI/ML infrastructure: feature stores (Feast, Tecton), vector databases (pgvector, Pinecone, Weaviate), or RAG pipelines for internal knowledge systems.

- Exposure to MLOps / LLMOps practices — evaluation harnesses, prompt versioning, offline/online metric tracking.

- Experience contributing to or operating a semantic layer that powers self-serve analytics and natural-language interfaces.

- Familiarity with Confluent Cloud, Kafka Connect, and Flink SQL.

- Open-source contributions or technical writing in the data engineering space.

Skills

Advanced SQL, Python, Dimensional Modeling, Data Warehousing (BigQuery preferred), dbt, Airflow / Cloud Composer, Kafka & Flink (or equivalent streaming), Terraform, GCP, CI/CD for data, Data Quality & Observability, AI-assisted development (Claude Code), applied GenAI for data workflows (text-to-SQL, RAG, agents).

In a world where technology never stands still, we understand that, dedication to our clients success, innovation that matters, and trust and personal responsibility in all our relationships, lives in what we do as IBMers as we strive to be the catalyst that makes the world work better.

Being an IBMer means you’ll be able to learn and develop yourself and your career, you’ll be encouraged to be courageous and experiment everyday, all whilst having continuous trust and support in an environment where everyone can thrive whatever their personal or professional background.

Our IBMers are growth minded, always staying curious, open to feedback and learning new information and skills to constantly transform themselves and our company. They are trusted to provide on-going feedback to help other IBMers grow, as well as collaborate with colleagues keeping in mind a team focused approach to include different perspectives to drive exceptional outcomes for our customers. The courage our IBMers have to make critical decisions everyday is essential to IBM becoming the catalyst for progress, always embracing challenges with resources they have to hand, a can-do attitude and always striving for an outcome focused approach within everything that they do.

Are you ready to be an IBMer?

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At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing and blockchain. Now it’s time for you to join us on our journey to being a responsible technology innovator and a force for good in the world.

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