Sr. / Lead Data Quality Engineer

Pipe Recruit; Santa Monica, Seattle (CA, WA); On-site; USD 120,000 - 160,000; Full time

Job summary

A leading data solutions firm is seeking a highly skilled Sr. / Lead Data Quality Engineer to ensure data accuracy and integrity. The ideal candidate will have over 10 years of extensive experience in Data Quality Engineering, proficient in SQL and Python, and be adept at conducting data profiling. Responsibilities include designing Data Quality checks, monitoring metrics, and collaborating with stakeholders to enhance data governance. This position is available for candidates located in Seattle, WA or Santa Monica, CA, and offers an on-site work environment.

Qualifications

• 10+ years of experience in Data Quality Engineering.
• Strong proficiency in SQL for data analysis.
• Advanced Python skills for automation and data manipulation.

Responsibilities

• Design and implement Data Quality checks for data pipelines.
• Conduct data profiling to uncover anomalies and trends.
• Monitor Data Quality metrics and flag anomalies.

Skills

Data Quality Engineering

Data Profiling

SQL

Python

Tools

Snowflake

PySpark

Airflow

Looker

Job description

About the job Sr. / Lead Data Quality Engineer

Job Title: Sr. / Lead Data Quality Engineer
Domain: Data Analytics / Data Science / Data Engineering
Location: USA Seattle, WA / Santa Monica, CA (Onsite)
Experience Required: 10 15 Years
Work Authorization: US Citizen / Green Card Holder Only

Overview:

Tavant is seeking a highly skilled and detail-oriented Sr. / Lead Data Quality Engineer to join our dynamic data team. This role demands an expert in data accuracy, integrity, and reliability, who thrives in a collaborative environment and is passionate about solving complex data issues. The ideal candidate will have deep technical expertise in Data Quality Engineering, strong analytical skills, and a proven track record of working with large-scale data systems.

Key Responsibilities:

• Design and implement robust Data Quality (DQ)checks and validation rules to ensure accuracy and consistency across data pipelines.
• Conduct data profiling to assess source data, uncover anomalies, and identify patterns or trends.
• Monitor Data Quality metrics, track trends, and flag spikes or drops in Key Performance Indicators (KPIs).
• Define and maintain thresholds for detecting and flagging data anomalies and inconsistencies.
• Collaborate with business and technical stakeholders to:
• Understand both explicit and implicit data quality requirements.
• Translate business needs into actionable data quality measures.
• Recommend process improvements to enhance data governance and quality.

Must-Have Skills:

• 10+ years of recent, hands-on experience in:
• Data Quality Engineering
• Data Profiling
• SQL (Strong proficiency for deep data analysis and issue resolution)
• Python (Advanced scripting skills for automation and data manipulation)
• Snowflake (Cloud-based data warehousing)
• Strong problem-solving skills to identify root causes of data issues and implement corrective measures.
• Experience in testing and validating data in large-scale systems.
• Job stability in past roles is essential.
• Candidate must be based in Seattle, WA or Santa Monica, CA.

Preferred / Nice-to-Have Skills:

• Experience with PySpark or Spark for distributed data processing.
• Familiarity with Airflow for data pipeline orchestration.
• Working knowledge of Looker or other Business Intelligence tools.

Candidate Profile:

You are a data enthusiast who:

• Is a natural problem-solver with a keen eye for detail.
• Loves working with data to identify inconsistencies and trends.
• Is highly analytical and tech-savvy, with the coding chops to build scalable DQ solutions.
• Communicates effectively with both technical and business stakeholders.
• Enjoys contributing to high-quality data governance practices and standards.