About
IBM Consulting Client Innovation Centers (CICs) are high-delivery environments where technologists build solutions for clients. The Associate Data Engineer will support the development and maintenance of data pipelines while collaborating with experienced practitioners in a hands-on, team-based setting.
Responsibilities : • Support the development and maintenance of data pipelines used for analytics, reporting, and machine learning • Assist with extracting, transforming, and loading (ETL/ELT) data from multiple sources into data platforms • Contribute to data cleansing, validation, and transformation activities using Python and SQL • Help prepare datasets for downstream consumption by analytics and data science teams • Support batch and, where applicable, near-real-time data processing workflows under guidance • Collaborate with data engineers, data scientists, and other team members in Agile delivery environments • Build data engineering skills through training, mentorship, and hands-on delivery experience • Work with functional and technical team members to help integrate data solutions into client business environments
Qualifications : Required : • Strong foundation in computer science fundamentals, including data structures and algorithms • Strong analytical and problem-solving skills with attention to data quality and reliability • Comfortable working onsite in a collaborative, team-based environment • Ability to work effectively in a technology-driven consulting environment where tools, platforms, and client needs evolve over time • Strong analytical and problem-solving skills, with the ability to approach complex tasks using structured, logical thinking • Ability to learn new systems and technologies quickly and apply them in a delivery setting • Proficiency in Python (preferred) or another programming language used for data processing • Hands-on experience using data manipulation tools such as pandas, NumPy, and SQL, gained through coursework, labs, projects, or internships • Ability to write clear, maintainable code for data transformation and processing tasks • Understanding of ETL/ELT concepts and how data moves from source systems to consumption layers • Familiarity with relational databases and SQL for querying and data manipulation • Basic understanding of data modeling concepts such as schemas, normalization, or dimensional models • Exposure to cloud-based data or analytics platforms (e.g., AWS, Azure, or Google Cloud) through coursework, labs, or projects • Familiarity with core cloud data services such as object storage, databases, or analytics services • Ability to translate business or functional requirements into technical solutions, with guidance from senior team members • Comfortable working onsite in a collaborative, team-based environment • Strong willingness to learn, accept feedback, and continuously improve • Familiarity with generative AI concepts, including basic modeling approaches, responsible use, and ethical considerations, gained through coursework, projects, or self-study
Preferred : • Exposure to distributed data processing tools such as Apache Spark or PySpark • Familiarity with modern data warehouse technologies (e.g., Snowflake, Redshift, BigQuery) • Exposure to streaming or event-based data concepts • Familiarity with version control tools such as Git • Basic awareness of how data engineering supports machine learning workflows
Company :
IBM is an IT technology and consulting firm providing computer hardware, software, infrastructure, and hosting services. Founded in 1911, the company is headquartered in Armonk, USA, with a team of 10001+ employees. The company is currently Late Stage.
Languages
- English
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