Software Engineer

Job Summary

Employment Type: Full time

Join us as a Data Engineer, where you will play a pivotal role in transforming raw data into actionable insights that drive strategic business decisions. In this role, you will leverage your expertise in Python to design, develop, and maintain robust data pipelines and data warehouses, ensuring data integrity and quality across the organization. You will be responsible for building and optimizing scalable ETL processes, collaborating with cross-functional teams to define and implement efficient data models, and monitoring data workflows for performance improvements. Additionally, you will implement data quality checks, maintain comprehensive documentation, and advocate for best practices in data management. Your efforts will directly contribute to enabling data-driven decision-making, ensuring our data infrastructure meets the evolving needs of the business, and keeping us at the forefront of our industry. If you thrive in tackling complex data challenges and have a passion for innovation, we invite you to join our dynamic team!

Required Qualifications

Education:

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Experience:

• 4+ years of experience in data engineering or a similar role, with a strong focus on building and maintaining data pipelines.

Technical Skills:

• Proficiency in Python, with a solid understanding of data structures, algorithms, and libraries commonly used in data manipulation (e.g., Pandas, NumPy).
• Strong experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, or similar), including database design, optimization, and performance tuning.
• Familiarity with data warehousing concepts and experience using platforms such as Amazon Redshift, Google BigQuery, or Snowflake.
• Hands-on experience with ETL tools (e.g., Apache Airflow, Talend, or custom Python scripts) for data extraction, transformation, and loading.
• Knowledge of data modeling and experience in designing efficient and scalable data architectures.

Problem-Solving Skills:

• Ability to troubleshoot and resolve complex data issues, ensuring data quality and reliability.

Preferred Qualifications

Cloud Services:

• Experience with cloud platforms (e.g., AWS, Google Cloud Platform, Azure) and familiarity with their data services, such as AWS Glue or Google Cloud Dataflow.

Big Data Technologies:

• Knowledge of big data technologies such as Apache Spark, Hadoop, or Kafka for processing large datasets.

Data Governance:

• Understanding of data governance, data privacy, and compliance standards (e.g., GDPR, HIPAA) and how they apply to data engineering practices.

Data Visualization Tools:

• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker) for creating actionable insights from data.

Version Control:

• Experience with version control systems (e.g., Git) and CI/CD practices for automated deployment of data pipelines.

Soft Skills

• Strong communication skills and the ability to collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders.

Certifications:

• Relevant certifications in data engineering or cloud platforms (e.g., Google Cloud Professional Data Engineer, AWS Certified Data Analytics) are a plus.

Physical Demand & Work Environment

• Must have the ability to perform office-related tasks, which may include prolonged sitting or standing.
• Must have the ability to move from place to place within an office environment.
• Must be able to use a computer.
• Must have the ability to communicate effectively.
• Some positions may require occasional repetitive motion or movements of the wrists, hands, and/or fingers.

Salary Range

$47.13 - $74.42 USD (Hourly)

Please note that the salary information provided herein is base pay only (gross); it does not include other forms of compensation which may or may not apply to this specific position, namely, performance-based bonuses, benefits-related payments, or other general incentives.