Senior – Data Engineer

Senior – Data Engineer

Requirements

• Experience in Google Cloud, SQL, Big Query, Hive/Spark, Unix Scripting, Python, Tableau and Looker.
• 5+ years of experience of working in a high growth analytics team.
• 2+ years of experience in data visualization tools such as Tableau, Looker.
• 2+ years of programming experience with at least one language such as Python, Scala, Java or other modern OOP programming language.
• Fluency in SQL, as well as an understanding of statistical analysis, and common pitfalls of data analysis. Basic understanding of query logic is a MUST.
• Experience with parsing, cleansing and querying unstructured data using Hive/Spark.
• Experience with optimization and automation using scripting.
• Strong problem-solving skills with an emphasis on product development.
• Experienced developing in cloud platforms such as Google Cloud Platform (preferred), AWS, Azure, or Snowflake at scale.
• Experience in designing data engineering solutions using open source and proprietary cloud data pipeline tools such as Airflow, Glue and Dataflow.
• Excellent written and verbal communication skills for coordinating across teams.
• Bachelor’s degree in Statistics, Computer Science, Business Administration or related field. Relevant experience in Product analytics will be a PLUS.

Responsibilities

• Consults with senior leadership/business partners to understand overall goals/functional objectives, decipher key business challenges, identify tactics to anticipate and mitigate business challenges/issues and develop potential success criteria.
• Builds and leads a team to execute on business area or category objectives.
• Owns complex projects end-to-end for a business area, category or prototype.
• Manages the development and implementation of prototypes and production-ready complex algorithms for complex projects.
• Collaborates with functional leadership and cross-functional teams to develop consultative solutions for complex projects for a business area, category or prototype.
• Responsible for crafting simple, dependable data pipelines and automated reporting to surface metrics.
• Design and implement big data architecture, data pipelines, reporting, dashboarding, data exploration, processes and quality controls to enable self-service Business Intelligence.
• Explores data to find actionable insights and makes product recommendations through funnels, long-term trends, segmentation, and more as necessary.
• Designs, builds, and maintains ETL pipeline of analytical data warehouse.
• Provides and supports the implementation of business solutions applying data modeling, SQL and data warehousing skills.
• Applies fluency in SQL, as well as a deep understanding of statistical analysis, and common pitfalls of data analysis.
• Develop automated scripts, build reusable tools using any programming language, preferably Python.
• Identify the bottlenecks of data flow and analysis, architect and implement solutions such as automation of data processing pipelines, optimizations of data queries, and enhancement of data visualization and interpretation.
• Keep current on big data and data visualization technology trends, evaluate, work on proof-of-concept and make recommendations on the technologies based on their merit.

Preferred Qualifications

• Data engineering, database engineering, business intelligence, or business analytics, ETL tools and working with large data sets in the cloud.
• Master’s degree in Computer Science or related field and 3 years’ experience in software engineering.
• Knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly.