Senior Data Engineer (Contract) - Data Quality & Systems Forensics

Dermalogica LLC; San Francisco (CA); Hybrid; USD 536,000 - 893,000; Full time

Job summary

Dermalogica in Carson, CA is seeking a senior, hands-on data engineer for a six-month, full-time contract. The role focuses on investigating how complex systems actually work, fixing root causes, and implementing controls across ERP, e-commerce, and data warehousing environments.

Hybrid or remote with PT overlap are options, with compensation ranging from $70K to $80K for the engagement. You will inherit a backlog of data quality issues, audit SQL/ETL processes, and drive data integrity

Qualifications

• 7+ years hands-on data engineering in production environments.
• Strong depth in debugging data discrepancies across systems.
• Experience with ERP data, e-commerce platforms, and data pipelines.
• Ability to trace data end-to-end and fix root causes.

Responsibilities

• Investigate and root-cause data discrepancies across source systems and warehouses.
• Trace data end-to-end to understand transformations and rules producing incorrect results.
• Own prioritized backlog from investigation through remediation and validation.
• Audit SQL jobs, ETL processes, and dependencies for fragile behavior.
• Identify and eliminate hardcoded rules and duplicated data.
• Replace fragile manual processes with governed pipelines.
• Build automated reconciliation and monitoring for data quality.
• Document data lineage, dependencies, and ownership.

Skills

Data engineering

Analytical skills

Forensic problem solving

Communication with stakeholders

Independent work

Tools

Microsoft SQL Server

T-SQL

ETL processes

BigQuery

Cloud data warehousing

Job description

Current job opportunities are posted here as they become available.

Location: Carson, CA (hybrid) or remote with strong Pacific Time overlap
Duration: 6 months, full-time
Compensation: $70K to $80K for the six-month engagement
Team: Global Data & AI

Dermalogica is looking for a senior, hands-on data engineer to help us strengthen the fundamentals of our global data environment.

This is not a traditional reporting role, and it is not primarily a greenfield data engineering role. We are looking for someone who is exceptionally good at investigating how complex systems actually work, finding where data has gone wrong, fixing the underlying issue, and putting controls in place so it does not happen again.

You will inherit a prioritized backlog of known data quality and integration issues across a hybrid environment that includes ERP systems, e-commerce platforms, marketplace data, SQL Server databases, ETL processes, cloud data warehousing, and downstream analytics.

The right person will be comfortable peeling back the layers of an unfamiliar system: starting with a number that does not make sense, tracing it through databases, views, stored procedures, integration jobs and source systems, determining exactly where and why it broke, and driving the issue through to resolution.

We are looking for someone with strong technical depth, forensic instincts, practical judgment, and the confidence to operate independently in an environment where documentation is sometimes incomplete and the answer is not always obvious.

• Investigate and root-cause data discrepancies across source systems, databases, integrations, data warehouses, and reporting layers.
• Trace data end-to-end to understand where transformations, mappings, filters, jobs, or business rules are producing incorrect results.
• Own a prioritized backlog of data quality issues from investigation through remediation, validation, backfill, and closure.
• Audit existing SQL jobs, stored procedures, ETL processes, dependencies, and transformation logic to identify fragile or undocumented behavior.
• Identify and eliminate hardcoded business rules, silent failures, incomplete loads, duplicate data, and other recurring sources of data quality problems.
• Correct issues at the appropriate architectural layer rather than applying downstream patches.
• Recover and backfill missing or incorrect historical data and reconcile results back to source systems.
• Improve customer, channel, product, and other master-data mappings where inconsistent logic is affecting reporting.
• Replace fragile manual data processes with governed, scheduled, and monitored pipelines where appropriate.
• Build automated reconciliation, feed-health checks, and alerting so data failures are detected quickly rather than discovered through manual review.
• Improve dependency management, reload processes, and change controls so upstream changes do not create unexpected downstream issues.
• Document critical data lineage, system dependencies, transformation logic, and ownership as the environment is cleaned up.
• Work closely with internal IT, Finance, market teams, external development partners, and vendors to drive issues to resolution.
• Communicate technical findings clearly to both technical and non-technical stakeholders.
• 7+ years of hands-on data engineering, database engineering, or closely related experience in production environments.
• Deep experience with Microsoft SQL Server and T-SQL, including complex queries, views, stored procedures, scheduled jobs, and production troubleshooting.
• Strong understanding of ETL/ELT pipelines, system integrations, database dependencies, and data warehouse architecture.
• Demonstrated experience diagnosing and resolving data integrity or data quality incidents, not only building new pipelines.
• Ability to take an ambiguous problem — for example, “these numbers do not reconcile” — and independently determine where, when, and why the problem occurred.
• Experience tracing data across multiple systems and determining the appropriate source of truth.
• Strong analytical and forensic problem-solving skills. You are comfortable digging through unfamiliar systems, testing assumptions, and following evidence until you understand the root cause.
• Strong practical judgment and common sense. You know when something technically works but does not make sense from a business or data perspective.
• Ability to make safe changes in shared production environments and understand downstream impacts before implementing them.
• Ability to work independently with limited direction and drive issues across multiple teams through completion.
• Clear written and verbal communication skills.
• Experience with BigQuery or another modern cloud data warehouse.
• Experience with SSIS, SQL Agent, or similar scheduling/orchestration technologies.
• Experience working with ERP data such as JD Edwards, Microsoft Dynamics NAV, or Business Central.
• Familiarity with commerce platforms such as Shopify or Amazon marketplace data.
• Experience working with financial or commercial datasets, including invoices, transactions, sales, returns, tax, accruals, or general-ledger data.
• Experience reconciling data between operational systems, financial systems, warehouses, and BI/reporting tools.
• Experience with data observability, automated reconciliation, data-quality monitoring, or building similar controls.
• Experience working with legacy systems, offshore development teams, external vendors, or environments where system knowledge is distributed across multiple groups.

You are naturally skeptical of data that does not make sense.

When you find a discrepancy, you do not stop when you find a workaround. You want to understand what created it, what else it may have affected, whether it has happened before, and how to prevent it from happening again.

You are comfortable opening an unfamiliar stored procedure, examining job history, comparing source tables, talking to Finance about what a transaction should represent, and challenging assumptions made by other technical teams.

You are methodical without being bureaucratic, technically rigorous without losing sight of the business problem, and comfortable working in systems that are not perfectly documented.

Most importantly, you know how to peel back the onion until you get to the real answer.

Over the six-month engagement, you will:

• Build a clear understanding of the critical data flows, jobs, dependencies, and transformation logic behind global reporting.
• Resolve and close the highest-priority data quality and integration issues.
• Correct historical data where necessary and establish confidence that key datasets reconcile back to their source systems.
• Reduce reliance on fragile manual processes and undocumented logic.
• Introduce automated reconciliation, monitoring, and alerting for critical data flows.
• Improve documentation, lineage, ownership, and change controls.
• Leave behind a substantially cleaner, more reliable, and easier-to-operate data environment with a clear process for managing any remaining issues.

The total expected compensation for this 6 month contract will range from $70K to $80K. The exact amount is determined by various factors including experience, skills, education, location, and budget.

Dermalogica is an equal opportunity employer committed to fostering an inclusive culture where all employees are valued, supported, and empowered to succeed.