Вакансія: Senior Analytics Engineer (в Рівне)

Загальна інформація про вакансію

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