About the Company is a leading global Ad Tech company focused on creating the most transparent and efficient path for advertiser budgets to translate into publisher revenue. The company’s proprietary contextual technology is at the forefront of programmatic advertising — the industry standard for digital ad buying across platforms. powers advertising solutions at massive scale across multiple formats including:
Display Advertising
Video Advertising
Mobile Advertising
Native Ads
Search Advertising
The platform supports major global publishers and Ad Tech businesses worldwide, helping them maximize monetization and advertising performance through advanced contextual and programmatic technologies.
Global Presence
U. S. Headquarters: New York City
Global Headquarters: Dubai
Offices and consulting partners across multiple international markets works with:
50+ Demand Partners
21 K+ Publisher Partners globally at Scale (Annual Impact)
125 B+ Ads Served
17 M+ URLs Monetized
1 B+ Ad Clicks Managed
6 T+ Ad Impressions Delivered
About the Role
Responsibilities will be structured to focus on execution and will be expected to be hands-on. Will include end-to-end product ownership including architecture, design, execution and management of a large and complex platform that records and analyzes large volumes of data. These will stretch from generating complex SQL to gain business insight out of the many levels of data, to writing detailed Stored Procedures that give split-second responses. The primary scope of this role including stored procedures, query optimization, schema design, indexing strategies, and data modelling across RDBMS systems.
Responsibilities
Own and optimize stored procedures, functions, triggers and views across MS SQL Server and My SQL
Design and evolve schemas with sound data modelling practices (3 NF, dimensional modelling, SCDs)
Deep index management — clustered, non-clustered, covering indexes, index fragmentation and rebuild strategies
Query plan analysis and tuning — execution plans, statistics, cardinality estimation
Enforce ACID compliance, manage transactions and isolation levels
Support data engineering team on big data pipeline integrations with RDBMS layer (Spark, Iceberg interop)
Work on ETL/ELT layers that feed into or read from RDBMS systems
Qualifications
Experience required for the role: 3-6 years
Required Skills
Strong expertise in MS SQL Server and My SQL, including development using stored procedures, user-defined functions, triggers, views, and cursors
Advanced proficiency in SQL programming, including window functions, CTEs, recursive queries, and set-based operations
Hands-on experience in query performance tuning, including execution plan analysis, statistics management, cardinality estimation, and use of index hints
Deep understanding of indexing strategies, including clustered and non-clustered indexes, covering and filtered indexes, and index maintenance/fragmentation handling
Solid knowledge of data modelling techniques, including normalization (up to 3 NF), dimensional modelling, and handling slowly changing dimensions (SCDs)
Strong grasp of database fundamentals, including ACID properties, transaction management, isolation levels, locking mechanisms, and deadlock resolution
Experience with table and index partitioning for managing large-scale datasets in relational databases
Understanding of ETL/ELT pipeline design and integration with relational database systems
Working knowledge of Apache Spark (Py Spark/Scala) for batch data processing and interaction with RDBMS
Familiarity with big data table formats such as Apache Iceberg or Hive and their interaction with database systems
Preferred Skills
Experience with database monitoring and performance tools (e.g., SQL Profiler)
Exposure to cloud-based database platforms such as Azure SQL, AWS RDS, or Aurora
Knowledge of CI/CD pipelines for database deployments
Familiarity with streaming platforms such as Apache Kafka for real-time data ingestion
Experience with Python scripting for database automation and maintenance
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Display Advertising
Video Advertising
Mobile Advertising
Native Ads
Search Advertising
The platform supports major global publishers and Ad Tech businesses worldwide, helping them maximize monetization and advertising performance through advanced contextual and programmatic technologies.
Global Presence
U. S. Headquarters: New York City
Global Headquarters: Dubai
Offices and consulting partners across multiple international markets works with:
50+ Demand Partners
21 K+ Publisher Partners globally at Scale (Annual Impact)
125 B+ Ads Served
17 M+ URLs Monetized
1 B+ Ad Clicks Managed
6 T+ Ad Impressions Delivered
About the Role
Responsibilities will be structured to focus on execution and will be expected to be hands-on. Will include end-to-end product ownership including architecture, design, execution and management of a large and complex platform that records and analyzes large volumes of data. These will stretch from generating complex SQL to gain business insight out of the many levels of data, to writing detailed Stored Procedures that give split-second responses. The primary scope of this role including stored procedures, query optimization, schema design, indexing strategies, and data modelling across RDBMS systems.
Responsibilities
Own and optimize stored procedures, functions, triggers and views across MS SQL Server and My SQL
Design and evolve schemas with sound data modelling practices (3 NF, dimensional modelling, SCDs)
Deep index management — clustered, non-clustered, covering indexes, index fragmentation and rebuild strategies
Query plan analysis and tuning — execution plans, statistics, cardinality estimation
Enforce ACID compliance, manage transactions and isolation levels
Support data engineering team on big data pipeline integrations with RDBMS layer (Spark, Iceberg interop)
Work on ETL/ELT layers that feed into or read from RDBMS systems
Qualifications
Experience required for the role: 3-6 years
Required Skills
Strong expertise in MS SQL Server and My SQL, including development using stored procedures, user-defined functions, triggers, views, and cursors
Advanced proficiency in SQL programming, including window functions, CTEs, recursive queries, and set-based operations
Hands-on experience in query performance tuning, including execution plan analysis, statistics management, cardinality estimation, and use of index hints
Deep understanding of indexing strategies, including clustered and non-clustered indexes, covering and filtered indexes, and index maintenance/fragmentation handling
Solid knowledge of data modelling techniques, including normalization (up to 3 NF), dimensional modelling, and handling slowly changing dimensions (SCDs)
Strong grasp of database fundamentals, including ACID properties, transaction management, isolation levels, locking mechanisms, and deadlock resolution
Experience with table and index partitioning for managing large-scale datasets in relational databases
Understanding of ETL/ELT pipeline design and integration with relational database systems
Working knowledge of Apache Spark (Py Spark/Scala) for batch data processing and interaction with RDBMS
Familiarity with big data table formats such as Apache Iceberg or Hive and their interaction with database systems
Preferred Skills
Experience with database monitoring and performance tools (e.g., SQL Profiler)
Exposure to cloud-based database platforms such as Azure SQL, AWS RDS, or Aurora
Knowledge of CI/CD pipelines for database deployments
Familiarity with streaming platforms such as Apache Kafka for real-time data ingestion
Experience with Python scripting for database automation and maintenance
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