InterWorks · 7 hours ago
Data Engineer
InterWorks is a people-focused tech consultancy that empowers clients with customized, collaborative solutions. The Data Engineering Consultant will work closely with clients to design and deliver scalable data platforms, guiding them through complex data decisions and implementing reliable data solutions.
Information Technology & Services
Responsibilities
Lead and participate in discovery conversations to understand client goals, constraints, and current-state data environments
Guide clients through data platform, architecture, and tooling decisions, clearly explaining options and tradeoffs
Design and deliver technical roadmaps that support scalable data and analytics platform adoption
Apply strong data modeling and engineering best practices to support analytics, reporting, AI, and machine learning use cases
Stay current on modern data engineering trends, cloud platforms, and emerging technologies
Design and build modern, reliable data pipelines and ETL/ELT frameworks
Architect cloud-native data infrastructure with a focus on scalability, maintainability, and data quality
Integrate and unify data from diverse sources including SQL databases, APIs, spreadsheets, and cloud storage
Own technical direction for client engagements, balancing best practices with real-world constraints
Collaborate closely with analysts, consultants, and client stakeholders to translate business needs into technical solutions
Deliver billable consulting services, including hands-on engineering work and client advisory engagements
Qualification
Required
5+ years of professional experience in data engineering, technical consulting, or a related field
Strong SQL skills and experience working with relational databases and cloud data warehouses
Hands-on experience with ETL/ELT workflows and data transformation frameworks
Solid understanding of data modeling best practices and data quality principles
Experience working in client-facing or consulting-style environments
Ability to translate complex technical concepts into clear, actionable guidance for non-technical audiences
Working knowledge of cloud platforms and modern data engineering architectures
Familiarity with DevOps concepts, CI/CD pipelines, and version control
Comfort navigating ambiguity and evolving requirements in a consultative environment
Strong problem-solving skills and a client-centered mindset
Preferred
Experience with cloud platforms such as AWS, Azure, or GCP
Familiarity with tools like Snowflake, Databricks, dbt, Fivetran, Matillion, or similar technologies
Working knowledge of Python or scripting for automation
Exposure to analytics, BI, or downstream data consumption use cases
Interest in AI and emerging technologies shaping the future of data engineering
Background in software engineering, systems integration, or analytics consulting