Data Engineer

Data Engineer

Location: Hanover, MD – Onsite
 

Job Summary

We are seeking an experiencedData Engineer to design, develop, and support enterprise data solutions focused on data conversion, ETL/ELT, operational analytics, production monitoring, and reporting. The ideal candidate will have strong expertise inSQL, Python, Snowflake, ETL/ELT tools, Tableau, and hands-on experience working with theSalesforce data model.

Key Responsibilities

Data Engineering & ETL

• Design, develop, test, and support scalable ETL/ELT pipelines.

• Build reusable utilities for data transformation, cleansing, validation, reconciliation, and exception handling.

• Develop and optimize advancedSQL and Python solutions.

• Support data conversion, migration, cutover, hypercare, and post-production reconciliation.

• Develop curated datasets for analytics and reporting.

Salesforce Data Engineering

• Work with Salesforce objects, schemas, relationships, and data dependencies.

• Analyze Salesforce data to support conversion, reporting, and production issue resolution.

• Develop advanced Salesforce reports and custom report types.

• Assess the downstream impact of Salesforce data and schema changes.

• Collaborate with Salesforce Administrators and Product Owners.

Analytics & Monitoring

• Analyze data-quality issues and recurring production failures to identify root causes.

• BuildTableau dashboards, scorecards, analytical datasets, and leadership reports.

• Develop monitoring reports, alerts, reconciliation views, and exception reporting.

• Quantify impacted records, transactions, customers, and business processes.

• Troubleshoot production data issues and monitor data pipeline performance.

Enterprise Data & Collaboration

• Develop and support cloud data warehouse and data lake solutions.

• Apply dimensional modeling and data warehousing best practices.

• Participate in code reviews, CI/CD, Git, testing, deployment, and documentation.

• Follow enterprise standards for data governance, security, privacy, lineage, and quality.

• Work closely with architects, Product Owners, business analysts, Salesforce teams, and other technical stakeholders in an Agile environment.

Required Skills

• 5+ years of enterprise data engineering experience.

• Strong experience developing productionETL/ELT pipelines and large-scale data integrations.

• Hands-on experience withSalesforce data, including standard/custom objects, relationships, extraction, reporting, and schema analysis.

• StrongSQL development and query optimization.

• Experience withSnowflake or a comparable cloud data platform.

• Experience withMatillion or similar ETL/ELT technologies.

• StrongPython or equivalent programming experience.

• Experience with operational reporting, analytics, dashboards, monitoring, or alerting.

• Experience working with technical and business stakeholders in an Agile environment.

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field, or equivalent experience.

Preferred Skills

• Salesforce data migration, conversion, or production support experience.

• Advanced Salesforce reporting and custom report types.

• Tableau dashboard development and analytical data-source design.

• Experience integrating Salesforce with ERP, finance, operational, or enterprise platforms.

• Snowflake architecture and performance tuning.

• Experience withMatillion, dbt, Informatica, or comparable platforms.

• Salesforce APIs, Bulk API, Data Loader, or change-data-capture concepts.

• Automated data-quality, reconciliation, monitoring, and alerting frameworks.

• Cloud data services and data governance.

• Familiarity with Salesforce Data Cloud concepts such as ingestion, harmonization, identity resolution, and data activation.

Technical Skills

• Salesforce Data Model, Objects & Relationships

• Snowflake & Advanced SQL

• Matillion / ETL / ELT

• Python & Data Automation

• Tableau

• Data Warehousing & Data Lakes

• Dimensional Modeling

• APIs & Data Integration

• Data Migration & Conversion

• Reconciliation & Data Quality

• Production Monitoring & Root-Cause Analysis

• Git / CI/CD / DevOps

• Data Governance, Security & Lineage

Core Competencies

• Strong analytical and problem-solving skills

• Clear communication with technical and business teams

• Cross-functional collaboration

• Ownership and accountability

• Ability to manage complex data environments

• Results-oriented approach

• Adaptability and continuous improvement mindset