Data Engineering & Analytics Specialist – Workforce Management

Location:  San Diego, CA

Employment Type:  Contract

Schedule:  Hybrid

About Our Client

Our client is a consumer-focused organization that relies on data, forecasting, capacity planning, and operational reporting to support workforce management decisions at scale. The team is taking ownership of critical production reporting assets that provide demand- and supply-side visibility for planning activities.

This opportunity supports a broader effort to improve the reliability, accuracy, and maintainability of production data products used by business and workforce planning stakeholders. The ideal candidate will be comfortable operating in a live production environment, resolving data issues under time pressure, and partnering across technical and business teams during a reporting-asset transition.

Job Description

We are seeking a hands-on Data Engineering & Analytics Specialist to own and maintain production reporting pipelines and dashboards supporting workforce management, forecasting, and capacity planning. This role will be responsible for the day-to-day ownership of demand-side reporting assets, including Qlik dashboards and their supporting Superglue pipelines.

The Data Engineering & Analytics Specialist will manage production pipeline logic, schemas, dashboard connections, documentation, and runbooks following the handoff from an existing Data Science & Analytics team. This individual will validate outputs against pre-migration baselines, troubleshoot discrepancies, support issue triage, and help close known reliability gaps in adjacent planning tools.

The ideal candidate has strong SQL and data-pipeline troubleshooting skills, experience supporting production BI dashboards, and the ability to work independently in an environment with incomplete documentation. This role will partner closely with technical teams, business-side planning stakeholders, and a supply-side reporting owner to ensure continuity, accurate reporting, and dependable production support.

Duties and Responsibilities

• Own the demand-side Qlik dashboard suite and the associated Superglue production data pipelines.

• Maintain pipeline logic, data schemas, dashboard connections, operational documentation, and runbooks.

• Validate pipeline outputs against established pre-migration baselines during the reporting-asset transition.

• Investigate, troubleshoot, and resolve data discrepancies, pipeline failures, and dashboard issues.

• Maintain the day-to-day availability, reliability, and accuracy of assigned production reporting assets.

• Participate in bug-triage meetings and provide technical input on production data and reporting issues.

• Serve as the first-line escalation point for owned reporting assets after transition from the Data Science & Analytics team.

• Troubleshoot pipeline dependency failures, race conditions, schema changes, data-quality issues, and dashboard-connectivity problems.

• Escalate complex production issues to the appropriate technical partners when additional support is needed.

• Build and maintain a defect inventory for known configuration-validation and error-handling gaps in adjacent planning tools.

• Support reliability improvements for ramp-optimizer and expert-planning tools.

• Track and help resolve known data-table issues, including field-definition discrepancies, intermittent pipeline race conditions, and downstream report-access tagging gaps.

• Partner with the outgoing Data Science & Analytics team to support knowledge transfer, documentation review, data lineage understanding, and production-process transition.

• Collaborate with workforce planning stakeholders who rely on reporting assets for demand, supply, forecasting, and capacity-planning decisions.

• Provide backup coverage for supply-side reporting assets and support reciprocal coverage planning to maintain operational continuity.

• Communicate production status, risks, issue resolution, and improvement recommendations to technical and business stakeholders.

Required Experience/Skills

• Strong SQL skills.

• Hands-on experience working with a cloud data lake or lakehouse environment, such as Databricks or an equivalent platform.

• Experience owning, maintaining, or supporting production BI dashboards.

• Experience with Qlik is strongly preferred; experience with comparable business intelligence tools will be considered.

• Experience working with ETL processes, data pipelines, and pipeline-support tooling.

• Experience troubleshooting and resolving production data pipeline issues.

• Ability to diagnose pipeline dependency failures, race conditions, schema drift, data-quality issues, and dashboard connectivity problems.

• Experience maintaining or supporting production data products with imperfect or evolving documentation.

• Ability to triage, prioritize, document, and escalate production issues effectively under time pressure.

• Strong analytical and problem-solving skills.

• Strong written and verbal communication skills.

• Ability to work independently while coordinating closely with cross-functional technical and business teams.

• Ability to communicate effectively with technical partners and business-side planning stakeholders.

Nice-to-Haves

• Experience with contact center, workforce management, or operational planning data.

• Familiarity with contact metrics, handle-rate metrics, forecast-versus-actual reporting, staffing concepts, and capacity-planning processes.

• Experience with a pipeline orchestration tool comparable to Superglue.

• Previous experience supporting a data-pipeline, dashboard, or reporting-ownership transition.

• Experience validating migrated reporting outputs against historical baselines.

• Experience developing or maintaining operational runbooks, data lineage documentation, and production support documentation.

• Experience identifying and tracking defects related to data configuration, access management, validation logic, or error handling.

• Experience partnering with data science, analytics, engineering, and business operations teams to improve production reporting reliability.

Education

Bachelor’s degree in Computer Science, Data Science, Statistics, Information Systems, or a related quantitative field.

Equivalent practical experience supporting production data pipelines, dashboards, and BI tooling will also be considered.

Pay & Benefits Summary

Pay Range:  Up to $65/hr W2

Call-to-Action

If you enjoy owning production data products, solving complex reporting issues, and improving the reliability of tools that influence workforce planning decisions, we encourage you to apply.

Data Engineering | Analytics | SQL | Qlik | Databricks | ETL | Data Pipelines | BI Dashboards | Workforce Management | Capacity Planning | Forecasting | Data Quality | Production Support | Pipeline Troubleshooting | Data Lakehouse