Senior Data Engineer

RESPONSIBILITIES

• Develop deep knowledge and understanding of the data assets available within our data platforms and act as the subject matter expert on the data and its utility for operational use.

• joining forces with the business, data engineering teammates and product development partners, candidate’s expertise in petabyte scale data in data lakes, data warehouses or data marts – in structured, semi-structured and unstructured formats – will deliver on the company’s Data and Analytics organization’s mission to enable data-driven decisioning within any action.

• Work directly with the developers, system architects, and users to review requirements and deliver best-practice database models.

• Work with stakeholders including the product, data and architecture teams to assist with data-related technical issues and support their data infrastructure needs.

• Provide proactive design, operational support, and governance for privacy and security policy for data.

QUALIFICATIONS

• Bachelor's Degree in Library Science, Information Systems, Finance, Information Technology or equivalent experience

• 5-7years of experience in Data Warehousing and Data Modeling with ETL/ELT,SQL

• Experience developing models in modern public data warehousing environments like Snowflake, Synapse, BigQuery, RedShift

• Experience using Data Modeling tools such as ERWIN or ER/Studio is a plus

• Proficient in Linux/Unix environments

• Experience developing dimensional models and running queries on edge databases such as Oracle , PostgreSQL, MariaDB/MySQL, or SQL Sever

• Strong understanding of Normalized/Dimensional model disciplines and similar data warehousing techniques.

• Strong experience working with ETL/ELT concepts of data integration, consolidation, enrichment, and aggregation in petabyte scale data sets.

• Expert in SQL and/or SQL based languages and performance tuning of SQL queries.

• Collaborate with Product and analytics teams on normalizing and aggregating large data sets based on business needs and requirements.

• Data auditing skills to verify data integrity, understand discrepancies and resolve them with the highest sense of urgency.

• Experience with various data storage technologies – e.g., RDBMS, columnar, tabular, document store, noSQL

• Experience with cloud-based data warehouses – e.g., Snowflake, BigQuery, Synapse, RedShift, etc

• Experience with Data Modeling tools is a plus – e.g., ERWIN or ER/Studio

• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.

• Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.

• Demonstrated ability to share findings to non-technical or senior executive individuals.

• Familiarity with Analytical/Reporting Solutions like Qlik Sense, PowerBI is a plus

• Any Public Cloud certification focused on data warehousing, preferred

• Any certification on specific database technology, preferred

Experience: 5-10 years