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Tier-1 consulting brand, metro location, generalist data engineer title, and broad experience band increase competition.
Core data engineering skills are highly transferable across industries despite consulting context.
Explicit years plus mandatory tech stack (Python, cloud, PySpark, SQL) yields moderately strict screening.
Develop, maintain, and monitor high-performance data engineering applications and pipelines enabling deployment of ML frameworks at scale.
Collaborate with consulting teams and clients to understand business challenges and deliver data-driven solutions across industries.
Lead data engineering best practices, develop proprietary tools, shape proposals, and maintain documentation for operational excellence.
Bachelor’s or master’s degree in Computer Science, Informatics, Data Science, or related quantitative discipline from a top academic program.
Proven experience designing and deploying large-scale cloud-native data solutions with tools like Python, SQL, PySpark, and cloud platforms (AWS, Azure, or GCP).
Work Experience Required: 0–8 years of relevant data engineering experience.
Ability to travel internationally as required.
Experienced in handling big data environments and implementing CI/CD pipelines and test-driven development for data engineering.
Capable of mentoring junior engineers and managing multiple priorities in fast-paced environments independently.
Skilled at client engagement and collaborating with cross-functional global teams to deliver measurable impact.