Position: Data Engineer /DBA
Company: Newfire Global Partners
Category: Data Science
Experience required: 5y
English level: upper

You Perfectly Match If you have:

- 5+ years of commercial experience with hand-on Data Architecting, Modeling and Warehousing.
- 5+ years experience with a modern Data Warehousing stack including Postgres and other equivalent modern technologies.
- Track record of working in Scrum / Agile software teams.
- Proficient in spoken and written English.
- Strong experience with SQL design and architecture best-practices (i.e. third normal form, index management, constraints, and foreign key relationships, etc.).
- Good understanding of common database administration tasks and concepts such as backup & restore, recovery models, integrity checks, and replication methods.
- Expertise in using Profiler traces, Extended events and other tools to find poorly performing code.
- Expertise in query tuning and performance optimization.
- Experience using data modeling tools like ERWin, Visio, etc.
- Strong understanding of modern SQL Server DR & scalability features. (i.e. Always On Availability Groups, Resource Governor, etc. preferred
Strong SQL abilities and experience with massive relational database systems.
- Strong knowledge of all traditional Data Warehouse-related components (Sourcing, ETL, Data Modeling, Infrastructure, BI, Reporting) and the modern tools to support those components.
- Ability to clearly explain and justify ideas when faced with competing alternatives.
- Ability to design, communicate and apply effective and  architectural design patterns across a wide range of technical problems.
- Familiarity with GIT and release engineering strategies.


Nice to have:  

- Bachelor’s degree or higher in a technical field of study.
- Experience with AWS-based database systems (RDS/Aurora, Redshift, etc...), No-SQL databases, Operational Data Sources, and Data Lakes is preferred but not required.
- Strong desire to maintain a high level of professional and technical knowledge by attending educational workshops; reviewing professional publications; establishing personal networks; benchmarking state-of-the-art practices; and participating in professional societies.
- Familiarity with the MPP Databases (Redshift or Vertica), Hadoop ecosystem, and HQL.
- Familiarity with continuous delivery and DevOps.
- Flexibility and creativity in solution design - including leveraging emerging technologies.

Your day-to-day activities: 

- Work as part of multifunctional teams to own the design and architecture of logical entity model of the client's suite of products.
- Convert logical models into physical data models employing sound database normalization techniques.
- Create physical database objects like tables and views with appropriate data types, foreign keys, constraints and upfront design and maintenance of proper indexes.
- Create and maintain easy to follow technical documentation of data models.
- Serve as a go-to resource for questions related to existing and proposed logical and physical data models.
- Perform T-SQL code reviews and ensure that new database code meets company standards for readability, reliability, and performance.
- Assist with resolving the performance of poorly executing stored procedures and queries.
- Support team initiatives by developing tools and identifying opportunities for process automation; assist in evaluation and selection of standard tools for the department.
- Conduct Data Warehousing learning sessions for the team to evangelize good design and T-SQL coding practices.
- Periodically review and manage company T-SQL coding standards.
- Support building and deploying the infrastructure for ingesting high-volume data from various sources.
- Supporting developing and maintaining the data-related scripting for build/test/deployment automation. 
- Research individually and in collaboration with other teams on how to solve problems.
- Partner with team and research, design, test, and evaluate new technologies and services as it applies to data warehousing and architecting.
- Partner with the team to maintain an organization-wide view of current and future strategy and approach as it applies to data warehousing and architecting.
- Provide leadership and expertise in the development of standards, architectural governance, design patterns, and practices in data warehousing and architecting.
- Identify and resolve bottlenecks and bugs.
- Support with Scrum / Agile software development approach (e.g., sprint, standups, retros, planning, pointing, grooming, etc.