Senior Database Engineer

MarketOnce

1d•$150,000 - $180,000

About The Position

As a Sr. Database Engineer, you’ll join a close-knit team building the future of a platform designed to power immersive digital experiences for our customers and partners. In this role, you will leverage deep technical expertise to design, optimize, and operationalize large-scale data solutions spanning distributed compute, datalake, Relational and Vector databases that ensure high performance, scalability, and reliability. You'll work across the full modern data stack — from Lakehouse foundations to real-time inference — enabling advanced analytics, semantic search, and AI-driven capabilities at scale.

Requirements

7+ years in data engineering, big data platforms, or a related discipline with hands-on production experience at scale
Located in Eastern or Central time zone; you will work extensively with a team member in the UK
Proven experience analyzing and tuning production database systems for performance and reliability
Expert-level SQL skills — complex joins, CTEs, window functions, query plan analysis, and optimization across both OLTP (PostgreSQL) and distributed engines (Spark SQL, Databricks SQL, Delta Lake)
Hands-on experience with data lake technologies and data pipeline frameworks (e.g., Azure Data Lake, Azure Data Factory, Databricks)
Deep expertise in Apache Spark — DataFrames, Spark SQL, UDFs, partitioning, broadcast strategies, and hands-on performance tuning experience
Data warehouse and visualization experience, including demonstrated strong Logical, Physical, and Dimensional Modeling skills
Solid command of Delta Lake internals — transaction log, schema enforcement, schema evolution, time travel, CDF, Z-ordering, liquid clustering, and OPTIMIZE/VACUUM operations
Strong PostgreSQL experience — schema design, indexing strategies, partitioning, EXPLAIN/ANALYZE tuning, and extensions including pgvector for similarity search
Strong Python skills — PySpark, pandas, async programming, building production data utilities
Strong understanding of reporting and BI solution design, including Power BI or similar tools
Experience in design of technology roadmaps and the transition from the current architectural framework to target architecture of the future
Excellent verbal and written communication skills to document and present data models, strategies, standards, and concepts to both business and IT audiences
Experience with the following tech & tools: SQL Engines: Azure SQL Server, Spark, Cosmos DB, PostgreSQL, Elastic Azure Technologies: Cosmos DB, SQL Database, Analytics, Azure Databricks, Data Factory, Fabric, Power BI, Azure Data Lake ETL Tools: Azure Data Factory, Azure Databricks, Azure Stream Analytics Lakehouse: Delta Lake, Delta Live Tables LANGUAGES: SQL, Python, PySpark

Responsibilities

Analyze and optimize production data solutions to identify and resolve issues related to performance, locking, and scalability
Write and optimize complex SQL across the full stack — Spark SQL for distributed transformations, PostgreSQL for transactional and analytical workloads, and Delta Lake for versioned, ACID-compliant table management
Design and build large-scale Spark and Azure Data Factory pipelines for batch and streaming ingestion, transformation, and feature engineering — leveraging both PySpark and Spark SQL for distributed processing at large scale
Design and develop data lake architectures including Medallion Architecture to support advanced analytics and large-scale data ingestion
Build and maintain production-grade data pipelines for efficient data movement and transformation across systems. Managing Delta table lifecycles, schema evolution, Z-ordering, time travel, and Change Data Feed to support reliable, performant analytics and OLTP and ML workloads
Design and operate hybrid storage patterns combining PostgreSQL for transactional workloads — with optimized schemas, indexes, CTEs, window functions, and partitioning — alongside Delta Lake Lakehouse layers for analytical and ML workloads
Design and implement reporting solutions that deliver actionable insights to business stakeholders
Communicate database and data architecture designs to business and technical audiences, including business users, program sponsors, database administrators, ETL and BI developers
Evaluate potential technology/tool solutions that meet business needs and facilitate internal and external discussions towards desirable outcomes
Collaborate with solution architects and project resources on systems integration and compatibility, while acting as a leader in coaching, training, and providing guidance
Create functional and technical documentation related to data architecture and business intelligence solutions
Provide technical consulting to application development teams during application design and development for highly complex or critical projects
Design data governance procedures to ensure compliance with internal and external regulations