Location/City: Atlanta, GA

To Power Smart Mobility for Every Driver and Vehicle, Everywhere

For decades, parking was a hassle. Then in 2008, ParkMobile launched with a simple goal: make parking easier. Today, our team is committed to creating tech-based solutions that power smart mobility and make parking hassles of the past obsolete. We do this by creating innovative solutions that connect parking and mobility ecosystems, eliminating friction while maximizing convenience and efficiency. At ParkMobile we offer agile frameworks and incentives for innovators and problem solvers, all at the perfect spot for work and play at the heart of midtown Atlanta.

We’re experiencing exciting growth. We’re looking for more people to join our team and help shape a product used by more than 50 million people.

We are seeking a highly skilled and experienced Data Engineer to join our dynamic team. As a Senior Data Engineer, you will play a crucial role in designing, building, and maintaining our data infrastructure, ensuring that data is accessible, reliable, and scalable for analytics and business decision-making.

Responsibilities:

1. Data Pipeline Development:

• Collaborate with cross-functional teams to understand data requirements and design data pipelines to ingest, process, and transform data from various sources.

• Develop, optimize, and maintain ELT (Extract, Load, Transform) processes to ensure efficient data extraction and loading.

• Implement data quality checks and monitoring mechanisms to ensure data accuracy, quality, and consistency.

2. Data Architecture:

• Design and maintain data storage solutions, such as data warehouses, data lakes, and database systems, that align with business needs and scalability requirements.

• Evaluate and recommend appropriate data technologies and tools to support data processing and analytics.

3. Data Modeling:

• Develop and maintain data models and schemas to facilitate data access and analytics.

• Collaborate with data scientists and analysts to define data requirements and create data models that enable advanced analytics and reporting.

4. Performance Optimization:

• Monitor and optimize data pipelines and database performance to ensure fast and efficient data retrieval and processing.

• Identify and resolve performance bottlenecks and data-related issues.

5. Data Security and Compliance:

• Implement and enforce data security best practices, ensuring the confidentiality, integrity, and availability of sensitive data.

• Ensure compliance with data privacy regulations and industry standards.

6. Documentation and Collaboration:

• Create and maintain documentation for data engineering processes, data pipelines, and data models.

• Collaborate with other teams, such as data scientists, analysts, and software engineers, to support their data needs and projects.

7. Continuous Learning and Innovation:

• Stay updated with the latest trends and technologies in data engineering and analytics.

• Identify opportunities for innovation and process improvements within the data engineering domain.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

• 3+ years as a Data Engineer, with a strong track record of designing and implementing data solutions.

• Proficiency in programming languages such as Python, Java, or Scala.

• Hands-on experience with data warehousing technologies (e.g., AWS Redshift, Google BigQuery, Snowflake) and ETL tools (e.g., dbt, Coalesce, Talend).

• Strong database knowledge, including SQL and NoSQL databases (e.g., PostgreSQL, MySQL, SQL Server, MongoDB, Cassandra).

• Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services.

• Excellent problem-solving skills and the ability to work effectively in a collaborative team environment.

• Strong communication skills to convey technical concepts to non-technical stakeholders.

• Experience with data governance, data security, and compliance is a plus.