Data Engineer

Dollar Tree•Chesapeake, VA

1d•$95,000 - $118,500•Onsite

About The Position

This is an exciting opportunity to join the Data & Analytics Delivery Organization at Family Dollar. The company is undergoing a major transformation, and data‑driven insights are playing a critical role in delivering the best possible customer experience. We are seeking a Data Engineer who combines strong business acumen with hands‑on technical expertise. This role requires someone who can partner with key stakeholders to understand business challenges and translate them into world‑class technical solutions using modern cloud technologies. You will be responsible for designing and building data engineering solutions on our cloud‑based data platform. The role includes contributing to technical design, developing scalable data pipelines, and supporting data engineering workloads.

Requirements

Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
3+ years of experience in data engineering or data analytics.
Strong understanding of RDBMS concepts with 3+ years of advanced SQL and data analysis experience.
2+ years of experience with Linux command‑line tools and scripting.
3+ years of Python development experience with expert‑level proficiency.
1+ year working with Big Data processing frameworks and tools.
Hands‑on experience with GCP services such as Cloud Storage, Dataflow, Pub/Sub, and BigQuery.
Strong proficiency in SQL, Python, Linux shell scripting, and data modeling.
Solid knowledge of data modeling techniques
Ability to analyze source systems and transform data to meet target data model requirements.
Experience working with large‑scale data warehouses (10+ TB) and high‑volume ETL/ELT workloads (50M+ records/day).
Demonstrated experience delivering end‑to‑end technical solutions within enterprise BI/Data Warehousing environments.
Experience with performance tuning and optimization across the data delivery pipeline—from ingestion through analytics.
Experience working in a Scrum/Agile environment and tools such as Jira.

Nice To Haves

Experience migrating data of various formats (JSON, delimited files, APIs, real‑time feeds) into Google BigQuery is strongly preferred.
Experience working with a data science workbench or ML development environment.
Familiarity with data engineering aspects of machine learning pipelines (e.g., data prep, splitting, feature engineering, scoring)

Responsibilities

Collaborate closely with stakeholders across product, architecture, development, business intelligence, and executive teams.
Analyze data from multiple sources and develop solutions to integrate data into the enterprise data ecosystem
Develop automated pipelines to ingest and process structured and unstructured data using both batch and streaming patterns with cloud‑native toolsets
Work with diverse datasets and technologies to understand cross‑system correlations, patterns, and data relationships
Build, schedule, and monitor data pipeline orchestrations
Implement automation to optimize compute and storage usage across the cloud data platform
Develop and enhance end‑to‑end monitoring and observability capabilities for cloud‑based data platforms
Support knowledge sharing, cross‑training, and onboarding activities for team members
Provide clear and frequent updates to stakeholders on progress, risks, and deliverables
Participate in daily Scrum standups and contribute to an agile development environment
Stay current on emerging trends and technologies in Data Warehousing and Analytics—particularly within retail.