Sr. Database Engineer
1 week ago
Key Responsibilities:
- 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. using Python/open source technologies.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and cloud database technologies.
- Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related
- technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and regions. Work with data and analytics experts to strive for greater functionality in our data systems.
- Test databases and perform bug fixes.
- Develop best practices for database design and development activities.
- Ability to quickly analyze existing SQL code and make improvements to enhance performance, take advantage
- of new SQL features, close security gaps, and increase robustness and maintainability of the code.
- Take on technical leadership responsibilities of database projects across various scrum teams
- Manage exploratory data analysis to support database and dashboard development
Required Skills:
- Expert knowledge in databases like PostgreSQL (preferably cloud hosted in any one or more cloud offerings like AWS, Azure, GCP), and any cloud-based Data Warehouse (like Snowflake, Azure Synapse) with strong programming experience in SQL.
- Competence in data preparation and/or ETL tools like snapLogic, MATILLION, Azure Data Factory, AWS Glue, and SSIS (preferably strong working experience in one or more) to build and maintain data pipelines and flows.
- Understanding of data modeling techniques and working knowledge with OLTP and OLAP systems
- Deep knowledge of databases, stored procedures, optimizations of huge data
- In-depth knowledge of ingestion techniques, data cleaning, de-dupe, and partitioning.
- Experience with building the infrastructure required for data ingestion and analytics
- Ability to fine-tune report-generating queries
- Solid understanding of normalization and denormalization of data, database exception handling, transactions, profiling queries, performance counters, debugging, database & query optimization techniques
- Understanding of index design and performance-tuning techniques
- Familiarity with SQL security techniques such as data encryption at the column level, Transparent Data Encryption (TDE), signed stored procedures, and assignment of user permissions
- Experience in understanding the source data from various platforms and mapping them into Entity Relationship Models (ER) for data integration and reporting
- Adhere to standards for all databases e.g., Data Models, Data Architecture, and Naming Conventions
- Exposure to Source control like GIT, Azure DevOps
- Understanding of Agile methodologies (Scrum, Kanban)
- Preferably experience with NoSQL database to migrate data into other types of databases with real-time replication.
- Experience with automated testing and coverage tools
- Experience with CI/CD automation tools (desirable)
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