Bangalore, Karnataka, India
Information Technology
Full-Time
Fulcrum Digital Inc
Overview
Advanced SQL Development And Optimization
Work closely with data architects, business analysts, and reporting teams to understand data requirements, translate them into technical specifications, and deliver effective data solutions.
Communicate complex technical concepts clearly and concisely to both technical and non-technical stakeholders.
Actively participate in team meetings and contribute to the planning and execution of data engineering projects.
Technical Leadership And Mentorship
- Design, develop, and optimize complex SQL queries and stored procedures in Oracle and SQL Server environments to efficiently extract, transform, and load (ETL) data for various analytical and operational needs.
- Implement advanced SQL techniques including window functions, common table expressions (CTEs), and subqueries to solve complex data manipulation challenges.
- Troubleshoot and resolve intricate SQL query performance issues, identifying root causes and implementing effective solutions.
- Proactively identify and address performance bottlenecks in SQL queries and data processing pipelines.
- Implement and manage indexing strategies (B-tree, bitmap, etc.) to optimize query performance for large datasets.
- Utilize database partitioning techniques (range, list, hash) to improve data manageability and query speed.
- Design and implement materialized views to pre-compute and store frequently accessed data for faster retrieval.
- Apply query rewriting techniques to improve the efficiency of SQL execution plans.
- Conduct thorough analysis of query execution plans using database-specific tools (e.g., Oracle Explain Plan, SQL Server Execution Plan) to identify areas for optimization and reduce resource consumption.
- Design and implement efficient and scalable data models (both relational and dimensional) to support analytical reporting, data warehousing, and operational systems.
- Apply best practices for database normalization and denormalization based on specific use case requirements and performance considerations.
- Collaborate with data architects to ensure data models align with enterprise data architecture standards and principles.
Work closely with data architects, business analysts, and reporting teams to understand data requirements, translate them into technical specifications, and deliver effective data solutions.
Communicate complex technical concepts clearly and concisely to both technical and non-technical stakeholders.
Actively participate in team meetings and contribute to the planning and execution of data engineering projects.
Technical Leadership And Mentorship
- Provide technical guidance and mentorship to junior data engineers on SQL best practices, indexing strategies, performance tuning techniques, and data modeling principles.
- Contribute to the development and maintenance of team standards and best practices for data engineering processes.
- Conduct knowledge transfer sessions and workshops to upskill team members in SQL optimization, data warehousing concepts, and DSS best practices.
- Implement and enforce data security measures, including role-based access control (RBAC) to ensure appropriate data access and prevent unauthorized modifications.
- Work with security teams to implement data encryption techniques (at rest and in transit) to protect sensitive information.
- Adhere to data governance policies and procedures to ensure data quality, integrity, and compliance.
- Stay up-to-date with the latest trends and technologies in data engineering, database systems, and performance optimization.
- Proactively identify opportunities for process improvements and automation within the data engineering workflow.
- Contribute to the evaluation and adoption of new tools and technologies to enhance the team's capabilities.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum of 5-7 years of hands-on experience in Data Engineering, with a strong focus on SQL development and optimization.
- Expert-level proficiency in writing and optimizing complex SQL queries for Oracle and SQL Server databases.
- Deep understanding of database performance tuning techniques, including indexing, partitioning, materialized views, and query rewriting.
- Proven experience in analyzing query execution plans and identifying performance bottlenecks.
- Solid understanding of data modeling concepts (relational, dimensional) and best practices for normalization and denormalization.
- Experience working with large datasets and data warehousing concepts.
- Strong analytical and problem-solving skills with a keen attention to detail.
- Excellent communication, collaboration, and interpersonal skills.
- Ability to work independently and as part of a team in a fast-paced environment.
- Experience with other database technologies (e.g., PostgreSQL, MySQL, NoSQL databases).
- Familiarity with ETL/ELT tools and frameworks (e.g., Apache NiFi, Informatica, Talend).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and cloud-based data warehousing solutions
- Knowledge of scripting languages like Python or Shell scripting for data manipulation and automation.
- Experience with data governance and data quality frameworks.
- Prior experience in a leadership or mentorship role.
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