Data Engineering Lead

As a Data Engineer, you will be responsible for transforming raw data from our applications into structured datasets for large-scale analysis and machine learning model training. You will work closely with our development, data science, and business intelligence teams to ensure data integrity, quality, and accessibility.

• Data Pipeline Development: Design, develop, and maintain scalable data pipelines to process raw data from various sources.

• Data Transformation: Clean, transform, and enrich data to create high-quality datasets suitable for analysis and machine learning.

• Collaboration: Work closely with product teams, software developers, data scientists, and analysts to understand data needs and deliver innovative solutions.

• Data Management: Ensure data accuracy, consistency, and reliability across all datasets.

• Optimization: Optimize data processes for performance and scalability.

• Documentation: Maintain comprehensive documentation of data pipelines, processes, and schemas.

  Working Conditions:

• 40 hours per week, with occasional, but rare, overtime

• Remote / Hybrid / Flexible Work Options Available

• Frequent interaction with developers, test automation engineers, QA, management, and members of other Verisk subsidiaries

• Some days we just leave the office and have fun team building activities!

• Regular team lunches!

• State of the art facility with basketball, volleyball, and gym

• Ping pong, foosball, fruit bowls, snacks

• Fun and energetic teams

• Time for innovation, Hack-A-Thons, and learning

 

• Educational Background: bachelor’s degree in computer science, Data Engineering, or a related field.
• Experience: 3+ years of experience as a Data Engineer or in a similar role.
• Technical Proficiency:
  • Programming Languages: Proficiency in Python, SQL, and familiarity with languages such as C# or Java.
  • Data Processing: Experience with ETL tools and frameworks (e.g., Apache Airflow, Luigi, DBT).
  • Big Data Technologies: Hands-on experience with big data technologies such as Hadoop, Spark, and Kafka.
  • Database Management: Strong knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB, Cassandra).
  • Cloud Platforms: Experience with cloud services (e.g., AWS, Google Cloud, Azure) and their data processing tools (e.g., AWS Glue, Google BigQuery).
  • AI: Familiarity and enthusiasm for bleeding-edge analytical enablement using tools such as Large Language Models and Prompt Engineering. 
• Data Warehousing: Knowledge of data warehousing concepts and solutions (e.g., Redshift, Snowflake).
• Version Control: Proficient with version control systems (e.g., Git).

Machine Learning: Understanding of machine learning concepts and experience working with data for ML model training. 

For over 50 years, Verisk has been the leading data analytics and technology partner to the global insurance industry by delivering value to our clients through expertise and scale. We empower communities and businesses to make better decisions on risk, faster.

At Verisk, you'll have the chance to use your voice and build a rewarding career that's as unique as you are, with work flexibility and the support, coaching, and training you need to succeed. 

For the eighth consecutive year, Verisk is proudly recognized as a Great Place to Work® for outstanding workplace culture in the US, fourth consecutive year in the UK, Spain, and India, and second consecutive year in Poland.  We value learning, caring and results and make inclusivity and diversity a top priority.  In addition to our Great Place to Work® Certification, we’ve been recognized by The Wall Street Journal as one of the Best-Managed Companies and by Forbes as a World’s Best Employer and Best Employer