Position Title: Senior Data Engineer

Department: Data Science

Reports To: Team Lead / Tech Lead

Work Location: On-site

Position Summary

The Senior Data Engineer is responsible for designing, building, and maintaining robust data pipelines and data warehouse solutions. This role works closely with data analysts, software engineers, and other stakeholders to ensure data is clean, reliable, and accessible for business insights. The ideal candidate will bring strong ETL development experience, proficiency in SQL and cloud platforms, and the ability to work independently on complex data initiatives.

Essential Duties and Responsibilities

Key responsibilities include, but are not limited to:

1. Design, develop, and maintain scalable ETL pipelines and data warehousing solutions using tools such as SQL Server, Redshift, and dbt.
2. Write advanced SQL queries and scripts for data extraction, transformation, and loading from various structured and unstructured data sources.
3. Collaborate with cross-functional teams to understand data needs and translate them into scalable and maintainable solutions.
4. Maintain and improve existing data models and data flows; implement changes to optimize performance and reduce redundancy.
5. Ensure data integrity, accuracy, and security throughout the data lifecycle.
6. Work with cloud-based platforms (preferably AWS) to deploy, manage, and monitor data services and pipelines.
7. Develop and maintain technical documentation related to data models, workflows, and systems architecture.
8. Perform data profiling, cleansing, and validation to ensure high-quality and reliable analytics.
9. Contribute to architectural decisions for enterprise data infrastructure and mentor junior data engineers when needed.
10. Stay current with emerging trends and technologies in data engineering and recommend improvements to the existing infrastructure.

Supervisory Responsibilities

1. None

Qualifications

To perform this role successfully, candidates must meet the following requirements:

Education & Experience

1. Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field (preferred).
2. Minimum of 5 years of hands-on experience as a Data Engineer or in a similar role.
3. Proven expertise in data warehousing concepts and ETL development tools (any).
4. Proficient in SQL Server, AWS Redshift, and dbt for data modeling and transformation.
5. Strong SQL scripting capabilities and intermediate Python programming skills.
6. Exposure to cloud technologies, particularly AWS (e.g., S3, Lambda, Glue, Redshift, etc.).
7. Experience in working with large-scale datasets and optimizing data pipelines for performance and scalability.
8. Strong analytical thinking and problem-solving skills with the ability to work in a fast-paced environment.

Language Skills

1. Ability to read and comprehend technical documentation and business requirements.
2. Ability to draft moderately complex documentation and communicate clearly with team members.
3. Strong verbal communication skills for both technical and non-technical audiences.

Mathematical Skills

1. Ability to apply mathematical concepts such as fractions, percentages, ratios, and proportions to practical problems.
2. Comfort with data profiling, statistics, and data quality metrics.

Reasoning Ability

1. Strong ability to troubleshoot and resolve complex data issues.
2. Ability to understand and solve ambiguous problems through structured thinking and analysis.
3. Ability to handle multiple priorities and deliver quality outcomes within tight deadlines.

Computer Skills

1. Proficient in database technologies, SQL coding, and ETL tools.
2. Comfortable using cloud services (AWS preferred), version control systems (Git), and development tools.
3. Familiarity with workflow orchestration tools (e.g., Airflow, Prefect) is a plus.

Certificates and Licenses

1. None required (Relevant AWS certifications are a plus)

Travel Requirements

1. Minimal travel (up to 5%) may be required for meetings, training, or conferences.

Work Environment

1. This role is based in a typical office setting with a climate-controlled environment.
2. Reasonable accommodations may be made for individuals with disabilities.
3. No substantial exposure to adverse environmental conditions.

Information Security & Privacy Compliance

1. Ensure the secure handling and storage of sensitive data.
2. Implement access control protocols and data encryption standards.
3. Maintain compliance with privacy regulations (e.g., GDPR, HIPAA) and internal data governance policies.
4. Participate in regular security audits and proactively address vulnerabilities in data systems.