Senior Database Analyst

About linqd. We power growth for some of the biggest names in the building products industry, helping them connect with more customers, expand market share, and achieve measurable results. We’re a 100% virtual organization built on relationships, accountability, and performance. We invest in our people with competitive compensation, healthcare options, continuous learning, and a supportive, performance-driven culture, because the work we do for our clients is only as strong as the team behind it. About the Role We are looking for a Senior Database Analyst to take ownership of two distinct sides of our data infrastructure: Stabilize and optimize our legacy SQL Server environment ('DMP'). Three Microsoft SQL Server instances, managed through Azure, hosting isolated per-client databases for our existing customer base. These servers need a clear-eyed operator to bring them back to health, fix accumulated performance issues, and keep them running reliably for the next several years while we transition workloads off them. These servers are also used for integrations with tools like Tableau, and through Azure functions, are responsible for syncing data to and from CRMs. Design the database layer for our modern platform. Greenfield architecture on AWS using PostgreSQL for transactional workloads and ClickHouse for analytical / OLAP workloads. You will work alongside our senior services architect to facilitate the implementation of a new structure for a long-term platform to eventually replace DMP in a modernized stack using ClickHouse, AWS, and Postgres. What You'll Do Legacy DMP Environment (Microsoft SQL Server / Azure) Audit the current state of the three DMP servers and produce a prioritized remediation plan for performance, stability, and maintainability. Diagnose and resolve accumulated issues: index bloat, missing/redundant indexes, parameter sniffing, lock contention, fragmented statistics, runaway jobs, and storage pressure. Enhance monitoring, baselining, and alerting on resource utilization, query performance, and job health through SolarWinds. Lead the rollout of Airflow on DMP to replace existing scheduling/orchestration that has caused us issues (e.g., lock contention from a SQL Server-based meta-scheduler). Manage the multi-tenant isolation model across per-client databases — backups, restores, capacity planning, and security. Keep DMP healthy for several years of continued production use while modern workloads migrate off it incrementally. Modern Platform (PostgreSQL + ClickHouse on AWS) Work with our senior services Architect on our multi-phase long-term platform implementation. Translating application and business requirements into scalable and well-thought-out Clickhouse structures (multi-tenant). Design PostgreSQL schemas for transactional workloads, with appropriate indexing, partitioning, and extension usage. With work, senior services architect to build out ingestion processes for high-volume data, batch, and streaming with idempotency, backfill capability, and clean separation between raw, staged, and serving layers. Model data for read performance: denormalized read models, aggregation tables, and pre-computed projections that keep dashboards and APIs fast as data volumes grow. Define the operational practices for the new stack: monitoring, alerting, deployment, schema migration, and capacity planning. Cross-Cutting Optimize queries and indexes through systematic analysis, execution plans, wait stats, and query logs. Guide backend and data engineers on writing database-friendly code and avoiding common anti-patterns. Lead incident response for database-related issues across both environments and convert postmortems into durable improvements. Make use of our internal AI/LLM tooling for database analysis, where it speeds up the work; we've built tooling specifically to assist with this kind of investigation. Required Qualifications 7+ years of professional database analysis and engineering experience with significant ownership of production systems at scale. Microsoft SQL Server, deep expertise: query optimization, execution plan analysis, indexing strategy, partitioning, T-SQL, statistics, locking/blocking, isolation levels, and HA configurations. You should be comfortable diving into a neglected SQL Server environment and knowing exactly where to look. PostgreSQL, strong working knowledge: query planning, indexes (B-tree, GIN, GiST, BRIN), MVCC, vacuum/auto vacuum tuning, partitioning, and relevant extensions. Columnar / OLAP database experience, production experience with at least one columnar engine. ClickHouse strongly preferred; substantial experience with Snowflake, BigQuery, Redshift, Druid, or Pinot is acceptable, provided you understand columnar storage internals (compression, sort keys, merge/compaction behavior) and can ramp on ClickHouse quickly. Cloud experience across both Azure and AWS, Azure for the legacy DMP environment (Azure-managed SQL Server, monitoring, networking, identity), AWS for the modern stack (RDS / Aurora Postgres, networking, IAM, observability). Big data instincts — track record designing and operating systems that scale into the billions of rows, with judgment on when to throw hardware at a problem versus re-architect. Strong SQL fundamentals across dialects, including window functions, CTEs, and the ability to read and reason about execution plans across engines. Preferred Qualifications Airflow experience, particularly migrating workloads onto it from existing scheduling systems. Python for tooling, automation, and data work. (We do not expect C# proficiency.) Docker for local development and deployment. Familiarity with Railway is preferred; otherwise, a strong willingness to learn is required, as it is our primary platform for modern infrastructure deployment. SolarWinds experience for database monitoring. Tableau familiarity and the data modeling considerations that make BI tools perform well against analytical backends. Familiarity with Parquet, Iceberg, Delta Lake, or open table formats/lakehouse architectures. Experience with streaming ingestion (Kafka, Kinesis, Event Hubs, CDC tools like Debezium). Experience working alongside or building LLM/agentic tooling that interacts with databases. Background in data quality and deduplication at scale (entity resolution, fuzzy matching, ML-assisted record linkage). Comfort with infrastructure-as-code (Terraform, Bicep) and CI/CD for database changes. Tech Stack Legacy environment: Microsoft SQL Server (3-instance DMP fleet), Azure, multi-tenant per-client database isolation Modern environment: PostgreSQL, ClickHouse, AWS, Docker, Railway Orchestration: Airflow (rolling out on DMP) Monitoring / BI: SolarWinds, Tableau Tooling: Python, Docker, internal AI/LLM tools for database analysis Where you’ll work This role is fully remote. linqd., is headquartered in Endicott, NY, with team members across the country.