Senior Database Analyst

Remote (United States)

About the Role

An experienced Database Analyst is needed to take ownership of two critical areas of the data infrastructure.

The first priority is stabilizing and improving a legacy database environment known internally as DMP. This environment includes three Microsoft SQL Server instances managed through Azure, with separate client databases supporting the existing customer base. These systems require a hands-on database specialist who can resolve accumulated performance issues, improve reliability, and keep the platform operating smoothly for the next several years while workloads are gradually migrated to a newer architecture.

The legacy environment also supports Tableau integrations and uses Azure Functions to synchronize data with customer relationship management systems.

The second priority is helping design the database layer for a modern platform being built from the ground up on AWS. This new environment will use PostgreSQL for transactional workloads and ClickHouse for analytical and OLAP workloads. Working closely with a senior services architect, the Database Analyst will help create a scalable, long-term structure that will eventually replace the legacy platform.

Employment Type: Full Time

Compensation: $119,000 - $140,000 per year

What You’ll Do

Legacy DMP Environment — Microsoft SQL Server and Azure

• Evaluate the current condition of three Microsoft SQL Server instances and create a prioritized remediation plan focused on performance, stability, and maintainability.
• Identify and resolve database issues such as index bloat, missing indexes, redundant indexes, parameter sniffing, lock contention, fragmented statistics, runaway jobs, and storage pressure.
• Improve monitoring, performance baselines, and alerting for resource usage, query performance, and scheduled job health using SolarWinds.
• Lead the implementation of Airflow within the legacy environment to replace existing scheduling and orchestration processes that have contributed to operational issues, including lock contention caused by a SQL Server-based meta-scheduler.
• Manage the multi-tenant isolation model across separate client databases, including backups, restores, security, and capacity planning.
• Maintain the health and reliability of the legacy environment during a multi-year transition as workloads are incrementally moved to the modern platform.

Modern Platform — PostgreSQL, ClickHouse, and AWS

• Partner with a senior services architect on a multi-phase implementation of the organization’s long-term data platform.
• Translate application and business requirements into scalable, carefully designed multi-tenant ClickHouse structures.
• Design PostgreSQL schemas for transactional workloads using appropriate indexing, partitioning strategies, and extensions.
• Help build ingestion processes for high-volume data across batch and streaming workloads.
• Ensure ingestion processes support idempotency, backfills, and clear separation between raw, staged, and serving layers.
• Design data models for strong read performance, including denormalized read models, aggregation tables, and precomputed projections.
• Keep dashboards and APIs responsive as data volumes continue to grow.
• Define operational standards for the new platform, including monitoring, alerting, deployments, schema migrations, and capacity planning.

Database Performance, Engineering Guidance, and Incident Response

• Optimize queries and indexes through systematic analysis of execution plans, wait statistics, and query logs.
• Advise backend engineers and data engineers on database-friendly development practices and common anti-patterns to avoid.
• Lead incident response for database-related issues across both the legacy and modern environments.
• Turn post-incident findings into durable technical improvements.
• Use internal AI and large language model tools for database analysis when they can accelerate investigation and troubleshooting.

Required Qualifications

• At least 7 years of professional database analysis and engineering experience, including significant ownership of large-scale production systems.
• Deep expertise with Microsoft SQL Server, including query optimization, execution plan analysis, indexing strategies, partitioning, T-SQL, statistics, locking and blocking behavior, isolation levels, and high-availability configurations.
• Ability to assess a neglected SQL Server environment, identify the most important issues, and establish a practical path toward greater stability and performance.
• Strong working knowledge of PostgreSQL, including query planning, B-tree indexes, GIN indexes, GiST indexes, BRIN indexes, MVCC, vacuum and autovacuum tuning, partitioning, and relevant extensions.
• Production experience with at least one columnar or OLAP database engine.
• Experience with ClickHouse is strongly preferred. Substantial experience with Snowflake, BigQuery, Redshift, Druid, or Pinot is also acceptable if you understand columnar storage concepts such as compression, sort keys, and merge or compaction behavior and can quickly learn ClickHouse.
• Experience with both Azure and AWS.
• Experience using Azure for SQL Server infrastructure, monitoring, networking, and identity management.
• Experience using AWS for modern database environments, including RDS or Aurora PostgreSQL, networking, IAM, and observability.
• Experience designing and operating systems that scale to billions of rows.
• Strong judgment about when to improve infrastructure capacity and when to redesign an architecture.
• Strong SQL skills across multiple dialects, including window functions, common table expressions, and the ability to interpret execution plans across different database engines.

Preferred Qualifications

• Experience with Airflow, especially migrating workloads from existing scheduling systems.
• Experience using Python for tooling, automation, and data-related work.
• Experience with Docker for local development and deployment workflows.
• Familiarity with Railway or a strong willingness to learn it, as it is the primary deployment platform for the modern infrastructure.
• Experience using SolarWinds for database monitoring.
• Familiarity with Tableau and the data modeling practices that help business intelligence tools perform efficiently against analytical databases.
• Familiarity with Parquet, Iceberg, Delta Lake, open table formats, or lakehouse architectures.
• Experience with streaming ingestion technologies such as Kafka, Kinesis, Event Hubs, or change data capture tools such as Debezium.
• Experience working with or building AI, LLM, or agent-based tools that interact with databases.
• Experience with data quality and large-scale deduplication, including entity resolution, fuzzy matching, or machine-learning-assisted record linkage.
• Experience with infrastructure-as-code tools such as Terraform or Bicep.
• Experience with CI/CD workflows for database changes.

Technology Stack

• Legacy Environment: Microsoft SQL Server, three-instance DMP fleet, Azure, and separate client databases within a multi-tenant isolation model.
• Modern Environment: PostgreSQL, ClickHouse, AWS, Docker, and Railway.
• Orchestration: Airflow.
• Monitoring and Business Intelligence: SolarWinds and Tableau.
• Tooling: Python, Docker, and internal AI and LLM tools for database analysis.