Senior Data Engineer – AdTech

Jobtailor

Arizona

Hybrid

USD 110,000 - 170,000

Full time

3 days ago

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Job summary

Jobtailor seeks a data engineer to design and build robust, scalable data-driven applications and cloud-native pipelines. You will own data modeling, ETL/ELT development, and performance tuning in a hybrid hub environment across major US cities.

Collaborate with analysts, product teams, and engineers, support both cloud and on-prem warehousing, and drive best practices in data management and governance.

Qualifications

3+ years of SQL and relational DBMS experience.
3+ years in cloud data engineering platforms (AWS, GCP, Azure, Databricks, Snowflake).
3+ years in on-prem data platforms (MS SQL Server, Oracle, Teradata).
Proficient in SQL, Python, and PySpark.
Hands-on data modeling, schema design, and data warehousing.
Troubleshoot data issues and apply performance improvements.
Ownership mindset and ability to work in a fast-paced, collaborative environment.
Excellent oral and written communication skills.
Bachelor's degree in CS or related field, or equivalent experience.
Hybrid schedule in hub locations: Chicago, Boston, NYC, Dallas, Phoenix, Hartford, Woonsocket.
Preferred: BigQuery, Teradata, Snowflake, Azure, AWS, or GCP experience.
Preferred: healthcare data environments.
Preferred: real-time data integration, CDC, or event-driven architectures.
Preferred: workflow orchestration and automation tools.
Preferred: cloud migration and hybrid data architectures.
Preferred: monitoring, observability, and operational support best practices.

Responsibilities

Design and build robust, scalable data-driven applications and cloud-native data pipelines.
Own the full data lifecycle, including data modeling and ETL/ELT development.
Perform performance tuning and troubleshoot data issues.
Partner with business stakeholders, analysts, product teams, and engineers.
Support cloud-based and on-premises data warehousing services.
Drive continuous improvement and implement best practices.

Skills

SQL

Python

PySpark

Data Modeling

ETL/ELT

Performance Tuning

Data Troubleshooting

Ownership

Communication

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

GCP

Azure

Databricks

Snowflake

Microsoft SQL Server

Oracle

Teradata

BigQuery

Workflow Orchestration Tools

Job description

Design and build robust, scalable solutions for data-driven applications, analytics, and business intelligence
Engineer scalable, cloud-native data pipelines
Own the full data lifecycle, including data modeling and ETL/ELT development
Perform performance tuning and troubleshoot data issues
Drive continuous improvement and implement best practices
Partner with business stakeholders, analysts, product teams, and fellow engineers
Support cloud-based and on-premises data warehousing services

Requirements

3+ years of experience working with SQL and relational database management systems
3+ years of experience in cloud data engineering platforms such as AWS, GCP, Azure, Databricks, Snowflake, etc.
3+ years of experience in on-premises data engineering platforms such as Microsoft SQL Server, Oracle, Teradata, etc.
Programming and modifying code in SQL, Python, and PySpark
Hands-on experience with dimensional data modeling, schema design, and data warehousing
Hands-on experience troubleshooting data issues
Hands-on experience with performance improvement techniques
Ability to identify and implement process improvements and best practices
Ability to take ownership and work in a fast-paced, collaborative, team-based support environment
Excellent oral and written communication skills
Bachelor's degree in Computer Science or a related field, or equivalent work experience
Must work a hybrid schedule in a hub location: Chicago area, Boston area, New York City, Dallas area, Phoenix area, Hartford CT, or Woonsocket RI
Preferred: Experience with BigQuery, Teradata, Snowflake, Azure, AWS, or GCP
Preferred: Experience supporting healthcare, PBM, or specialty pharmacy data environments
Preferred: Familiarity with real-time data integration, CDC, or event-driven data architectures
Preferred: Experience with workflow orchestration and automation tools
Preferred: Exposure to cloud migration initiatives and hybrid data architectures
Preferred: Experience with monitoring, observability, and operational support best practices

Core Competencies

Demonstrates expertise in designing and building scalable data-driven applications and cloud-native data pipelines, with a strong focus on data modeling, ETL/ELT development, and performance tuning. Proficient in collaborating with cross-functional teams and implementing best practices for data management and warehousing.

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