Back
Mid-level metro data role with common stack and broad requirements drives high candidate competition.
Technical data engineering skills (SQL, PySpark, cloud) are highly transferable across industries.
Explicit 4-6 years plus mandatory Databricks/Redshift/AWS skills cause moderate shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop complex data solutions using SQL, Python, PySpark, Databricks, AWS, S3, and Redshift across multiple client projects.
Own end-to-end responsibilities in the project lifecycle including solution design, development, testing, and operational management.
Collaborate with teams and support project management tasks while providing transparent progress updates to stakeholders.
4-6 years of relevant work experience in data engineering or analytics project delivery.
Hands-on experience with SQL, Python, PySpark, Databricks, AWS S3, Redshift, and ETL tools such as Hadoop, Informatica, Talend, or SSIS.
Experience in data warehousing, cloud platforms familiarity (AWS preferred).
Knowledge or experience in the pharma domain is a plus but not mandatory.
Experienced mid-level data engineer comfortable leading technical ownership across project phases.
Strong expertise in cloud-based data platforms and ETL pipelines with ability to manage complex, multi-client engagements.
Consulting mindset with ability to communicate solutions effectively and support project management activities.