Data Engineer

I. Job Summary: The Data Analytics Engineer will be responsible for building and maintaining the data layer across the analytics stack from end to end. This role involves working closely with cross-functional teams from data engineering to analytics and visualization, delivering robust Business Intelligence solutions. The engineer will apply software engineering best practices such as version control, automated testing, documentation, code reviews, and continuous integration to ensure a high-quality data stack. Responsibilities include building data pipelines, creating data visualizations, and supporting teams in analyzing large volumes of data. The role covers tasks ranging from data collection and reporting to investigative analysis and building advanced models such as machine learning and computer vision.

II. Roles & Responsibilities: Manage the analytics data warehouse and implement analytical database design principles and business process best practices. Develop and support data pipelines, data lake, and data warehouse solutions; unlock value from data to support business decisions. Deliver clean data sets and products to product owners, analytics teams, and end users. Model data to create straightforward data APIs enabling front-end developers to connect visual components easily. Maintain and monitor data pipeline services and business intelligence platforms. Apply engineering best practices to deliver well-defined, tested, documented, and code-reviewed shared data sets. Identify, design, and implement process improvements—automation, optimizing data delivery, and infrastructure redesign for scalability. Support analytical requests cross-functionally from internal and external stakeholders. Create and maintain optimal data pipeline architecture. Assemble complex data sets meeting functional and non-functional business requirements. Build infrastructure for data extraction, transformation, and loading from diverse sources using ingestion techniques and AWS technologies. Develop data tools for analytics and data science teams to build and optimize products as industry leaders. Collaborate with data and analytics experts to enhance functionality in data systems. Establish scalable, efficient, automated processes for large-scale data analyses, model development, validation, and implementation. Solve complex data challenges and deliver actionable insights to achieve business goals. Create data products that boost analytics and data scientist productivity.

III. Years of Experience: 2 to 5+ years of relevant experience as an analytics engineer, data scientist, data engineer, or related role.

IV. Educational Qualification & Certifications (Optional): Bachelor’s degree in Computer Science, Information Systems, or related field.

V. Skill Set Required: Must have: Experience developing data solutions on cloud computing platforms, preferably GCP. 2+ years hands-on experience with frameworks such as Python, Java, or Scala. Skills in Python; Google BigQuery, Google Storage, Cloud Composer, Dataflow; Google PubSub; SQL; Ansible; Tableau APIs; Jenkins; and Shell scripting. Nice to have: Experience with Data Warehouse and ETL migrations. Advanced SQL skills and familiarity with various relational databases and complex query authoring. Experience with Scala, Python, PySpark, Java, REST API, Microservices, etc. Experience in restaurant or retail operations is preferred but not mandatory.