Data Engineer

About the Company :

Trademarkia is a global intellectual property law firm and the largest trademark filing law firm in the United States with over 120,000 clients in over 80 countries. We were founded in 2009. The world's largest visual search engine for trademarked logos, names, and slogans. Trademarkia offers free software and technology for seamless trademark searches, filings, monitoring, and legal automation processes. We are dedicated to making the law accessible to everyday people through our unique approach, including Google Meet/Zoom, and 24/7 legal support.

About the role:

We are seeking a highly skilled and experienced Data Engineer to join our team for the development and optimization of our data infrastructure. The ideal candidate will have a strong background in designing scalable ETL/ELT data pipelines, integrating diverse data sources, and optimizing data workflows to ensure efficiency and reliability.

In this role, you will be responsible for building and maintaining robust data architectures, implementing data quality checks, and ensuring compliance with security standards. The candidate should be proficient in working with SQL and NoSQL databases, designing efficient data models, and collaborating with cross-functional teams, including Backend Engineers, Frontend Engineers, Quality Engineers, Design Engineers, data scientists, and business stakeholders, to deliver impactful data solutions.

This is an exciting opportunity to work in a fast-paced, entrepreneurial law firm where you'll leverage cutting-edge technologies and drive innovation in legal tech through engineering useful tools, focusing on automation, performance optimization, and continuous improvement.

Key Responsibilities:

• Build and maintain robust ETL/ELT data pipelines.
• Implement transformation logic to convert raw data into meaningful insights.
• Develop automated workflows for reliable data processing.
• Develop specialized data pipelines for ML workflows, including feature stores, training data versioning, and scalable inference infrastructure
• Implement comprehensive data quality checks and monitoring systems.
• Create monitoring dashboards to visualize key performance metrics.
• Create automated systems to detect anomalies and clean, normalize and standardize data.
• Design scalable data architecture and Ensure system adaptability to evolving business needs.
• Create and optimize database schemas for performance and for data intensive processes for stakeholders.
• Implement indexing strategies and optimize query to improve performance.
• Design recovery procedures to restore data , handle database maintenance and upgrades including migrations.
• Ensure data security and consistency across the organization.
• Create data cleaning scripts to address inconsistencies to maintain data integrity and standardization.
• Integrate data from various sources, with an understanding of major cloud platforms like AWS or Azure.
• Build and manage data pipelines using Redshift, S3, and Azure Data Factory.
• Ensure data lineage tracking to trace data origins through maintained logging documentation.
• Maintain compliance standards.
• Mentor junior engineers and provide technical guidance and best practices.

Requirements :

• Bachelors or Master’s degree in Computer Science, Data Engineering, or a related field.
• Minimum 1-3 years of experience in data engineering or a similar role.
• Proficiency in data pipeline tools such as Apache Spark,Hadoop.
• Strong SQL and database management skills (e.g., PostgreSQL, MySQL, ElasticSearch ,QDrant ,RedShift and similar).
• Experience with cloud platforms like AWS, Azure and GCP.
• Knowledge of programming languages such as Python, Scala, R etc .
• Excellent problem-solving abilities, strong collaboration and communication skills, and a knack for mentoring junior engineers.
• Familiarity with data governance, compliance regulations, and security best practices.