Solutions Engineer Jobs

About The Position

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, software engineering, or a related technical discipline; equivalent experience, education, training, or certifications may be considered.
• Experience in database administration, data engineering, data architecture, or a related technical role.
• Experience designing or supporting enterprise data warehouses, data lakes, lakehouses, or comparable platforms.
• Experience developing ETL/ELT processes, data pipelines, transformations, and system integrations.
• Experience with legacy data migration, mapping, profiling, cleansing, reconciliation, validation, and remediation.
• Proficiency with SQL, relational database design, normalization, indexing, query optimization, backup and recovery, and performance tuning.
• Experience developing Power BI data models, datasets, dashboards, reports, and refresh pipelines.
• Knowledge of data quality, governance, metadata, lineage, security, and access-control principles.
• Ability to manage competing priorities and deliver reliable support within an estimated commitment of 75–80 hours per month.
• Must comply with applicable security, privacy, data-handling, background-screening, and customer-access requirements.

Nice To Haves

• Experience with Microsoft Azure, Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, Databricks, AWS, Google Cloud Platform, or comparable cloud data platforms.
• Experience implementing streaming, event-driven, telemetry, or real-time data-ingestion solutions.
• Experience with data cataloging, master-data management, and data-governance tools.
• Experience supporting public-sector, regulated, criminal-justice, or security-sensitive environments.
• Familiarity with DevOps, DataOps, CI/CD, source control, automated testing, and infrastructure-as-code practices.
• Relevant cloud, database, data-engineering, or Power BI certifications.

Responsibilities

• Design, develop, and maintain an enterprise data warehouse, data lake, or comparable platform for structured, semi-structured, and unstructured data.
• Define data models, schemas, metadata, integration patterns, storage approaches, and lifecycle-management practices.
• Establish standards for data ingestion, transformation, storage, access, retention, lineage, cataloging, quality, and security.
• Develop and maintain scalable ETL/ELT pipelines for batch, near-real-time, and real-time processing.
• Design secure, reliable interfaces among enterprise applications, reporting platforms, analytics tools, and data repositories.
• Plan, execute, document, and support migration of legacy data to the enterprise data environment.
• Assess source-system structures, data quality, business rules, integration dependencies, and technical constraints.
• Develop data mappings, transformation rules, migration procedures, reconciliation methods, validation criteria, and rollback plans.
• Migrate and validate data associated with OMS, PIC, PAC, IIMS, SSO, and other assigned applications.
• Perform data profiling, cleansing, standardization, deduplication, reconciliation, and exception resolution.
• Produce validation results, discrepancy logs, remediation recommendations, and migration-completion documentation.
• Develop and maintain Power BI reporting pipelines, semantic models, datasets, dashboards, and reports.
• Implement telemetry-based reporting for application activity, system health, performance, and operational metrics.
• Develop real-time and near-real-time ingestion workloads for reporting, monitoring, analytics, and decision support.
• Optimize reporting models, refresh processes, queries, and dashboards for performance, security, accuracy, and usability.
• Work with stakeholders to define reporting requirements, key performance indicators, data definitions, and dashboard enhancements.
• Design, configure, administer, maintain, optimize, and operationally support assigned databases and data platforms.
• Monitor database health, availability, capacity, storage, performance, query efficiency, replication, backups, and telemetry.
• Resolve performance issues using indexing, query tuning, partitioning, caching, archiving, configuration improvements, and capacity planning.
• Perform database maintenance, including backup and recovery validation, integrity checks, statistics maintenance, patch coordination, and monitoring.
• Implement and maintain database security controls, including role-based access control, least-privilege access, authentication, authorization, encryption, auditing, and logging.
• Provide recurring operational support and respond to database or data-pipeline issues; perform maintenance, releases, migrations, or incident response outside normal business hours when required.

Benefits

• 401(k)
• 401(k) matching
• Flexible schedule
• Flexible work from home options available