Senior Analytics Engineer

Required Skills

• 5+ years of experience in data analytics engineering field
• 5+ years of experience building processes supporting data transformation, data structures, metadata, dependency, and workload management.
• 5+ years of experience working on data warehousing platforms (Snowflake, Redshift, Bigquery, etc) including data transformation, data model design and query optimization strategies
• Solid understanding of data modeling and database design principles.
• Experience with DBT is highly valuable.
• Proficiency with SQL and experience with object-oriented/object function scripting languages (Python, Java, C ++, Scala).
• Experience with data pipeline and workflow management tools: Airflow, Azkaban, Luigi is valuable.
• Experience with BI tools like PowerBI, Tableau.
• Critical thinking: Analytical, conceptual and implementation skills. Ability to analyze business requirements in various business functional areas and translate them into conceptual, logical, and physical data models.
• Strong collaboration skills
• Passion for learning
• Excellent communicator, both verbal and written, in English. Comfortable communicating high level concepts to senior stakeholders whilst also being able to delve into the detail of complex changes when required.
  Key Responsibilities
• Delivering high-quality Data solutions for client in accordance with the agreed SLAВґs and within the budget
• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Follow and maintain operational and control procedures as a part of an agile team
• Help in the design and modeling of the Data in an Enterprise Data Platform and provide effective solutions in a cloud environment