Data Consultant

Role overview This role focuses on designing, building, and maintaining data pipelines and infrastructure for client engagements. The work covers end-to-end data solutions, integrating structured and unstructured sources into unified views for analysis, and collaborating with cross-functional teams. It is a hands-on engineering position with strong requirements-gathering and agile delivery components.

Responsibilities - Design, develop, and maintain scalable ETL pipelines that process large volumes of data from diverse sources. - Build and optimize data storage solutions such as data lakes and warehouses to support efficient retrieval and processing. - Integrate structured and unstructured data from internal and external systems into a single analytical view, with validation, cleansing, and transformation steps. - Collaborate with product managers and stakeholders to gather requirements and translate them into technical solutions. - Participate in Agile ceremonies including sprint planning, daily stand-ups, and sprint reviews, adapting to changing priorities. - Write unit and integration tests, debug applications, and resolve defects and performance bottlenecks while maintaining documentation.

Requirements - Bachelor's degree in Computer Science, Engineering, or a related field. - 3+ years of experience in data engineering or a closely related role. - Proficiency in Python and experience with SQL databases such as MySQL or PostgreSQL, as well as NoSQL databases such as MongoDB. - Familiarity with frameworks and libraries like Flask, Databricks, pandas, Spark, PySpark, and machine learning tools such as scikit-learn and OpenCV. - Experience with ELK stack, Redis, distributed task queues, and ETL or ELT tools across at least one cloud data engineering stack (AWS, Azure, or GCP). - Competence with Linux, shell scripting, Git-based workflows, and software engineering design patterns and best practices.

Nice to have - Effective written and verbal communication skills for collaborating in team settings. - Adaptability and willingness to learn new cloud and ETL/ELT tools as project needs evolve.