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Data Science1 month agoRemote

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Data Engineer - Temporary Worker

data engineeringSQLcloud data warehouseSnowflakeBigQueryDatabricksAmazon RedshiftAzure SynapsedbtELTETLPythonCI/CDGitApache AirflowDagsterPrefectAzure Data FactoryAI coding assistantsGenAICustomer 360data pipelinesdata modelingdata governancedata privacyTerraformTableauPower BILookerMarketing TechnologyCustomer Data Platformsmachine learningAgileJira

Key details

Salary

$40 – $48

Employment type

Full-time

Seniority

Mid-level

Years experience

2-4

Location

Maryland, United States

Full job description

Temporary W2 position based in the United States. Data Engineer role focused on building and operating modern data platforms for customer data warehouses. Responsibilities include designing cloud data warehouse architecture, building and maintaining SQL transformations and ELT/data pipelines, engineering customer features, and assembling unified customer profiles for downstream systems such as CDPs, CRMs, analytics, and data science teams. Requires 2-4+ years experience with SQL, cloud data warehouses (Snowflake, BigQuery, Databricks, Redshift, Azure Synapse), ELT/ETL tools (dbt, Talend, Informatica, Matillion, SSIS), source control (Git), CI/CD, data pipeline orchestration (Airflow, Dagster, Prefect, Azure Data Factory), Python scripting, and familiarity with AI coding assistants. Preferred skills include cloud platforms (AWS, GCP, Azure), infrastructure-as-code (Terraform), BI tools, campaign tools, and machine learning feature engineering. Hourly pay range $40-$48. Eligible for paid holidays and sick time per policy. No other benefits.

What you'll do

  • Contribute to the design of cloud data warehouse architecture and the conformed customer data model
  • Build and maintain SQL transformations, data models, and ELT/data pipelines that ingest, rationalize, and enrich customer data
  • Leverage common frameworks, reusable components, and AI-assisted development tools to accelerate delivery
  • Apply development standards, version control, and engineering best practices
  • Engineer customer features and assemble unified customer profiles for downstream CDP, CRM, analytics, and data science consumption
  • Perform development, unit and data-quality testing, and peer code review
  • Automate and orchestrate data pipelines, and manage code from development to production through source control and CI/CD
  • Use AI coding assistants and GenAI tooling responsibly to improve productivity, code quality, and feature development
  • Deliver high-quality, well-tested code and design documentation with minimal supervision
  • Be versatile and willing to take on new challenges across different projects and technologies
  • Ship reliable, automated pipelines that meet data-quality and delivery expectations
  • Mentor and provide technical guidance to other developers
  • Maintain a high sense of urgency to deliver on time

Requirements

  • 2–4+ years building data pipelines and SQL transformations on a major RDBMS and/or cloud data warehouse
  • Strong SQL and database programming skills, including query performance tuning and optimization
  • Hands-on experience with ELT/ETL and data transformation tooling
  • Strong understanding of relational and dimensional data modeling and conformed/customer (Customer 360) data models
  • Proficiency with source control (Git) and branching workflows, plus CI/CD for automated dev-to-prod deployment
  • Understanding of secure data exchange and file management (sFTP, PGP encryption)
  • Knowledge of data privacy and governance practices
  • Experience with data pipeline orchestration and automation
  • Familiarity with software engineering methodologies (Agile/Scrum), issue tracking (Jira), and full software development lifecycle
  • Understanding of core cloud and IT concepts — compute, storage, networking, and backups
  • Proficiency in Python for data engineering and scripting; comfort with Bash and command-line workflows
  • Solid communication skills, both verbal and written
  • Experience using AI coding assistants (e.g., GitHub Copilot) and working knowledge of GenAI/LLM concepts

Tech stack

SQLSnowflakeBigQueryDatabricksAmazon RedshiftAzure SynapsedbtTalendInformaticaMatillionSSISGitCI/CDsFTPPGP encryptionApache AirflowDagsterPrefectdbt CloudAzure Data FactoryPythonBashGitHub CopilotAWSGCPAzureTerraformTableauPower BILookerMicroStrategyAdobe CampaignSalesforce Marketing CloudBrazeUnicaRedPointJira

Benefits

Paid holidays in accordance with dentsu policySafe and sick time

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