Data Engineer

Solvd is looking for a highly skilled Data Engineer to help design and build modern data platforms that support large-scale risk and compliance initiatives for enterprise clients. In this role, you will architect and implement scalable data systems, real-time pipelines, and analytics capabilities that transform complex datasets into actionable insights.

You will partner with cross-functional teams—including data scientists, software engineers, and product stakeholders—to enable reliable, high-quality data solutions. This role requires strong technical depth in big data technologies, AWS services, and distributed systems, along with the ability to understand business needs and contribute to strategic decision-making.

What you will do

Data Architecture and Platform Development

• Design, build, and optimize scalable data infrastructure for risk and compliance workloads
• Develop batch and streaming pipelines using modern big data technologies
• Implement robust ETL and ELT workflows across diverse structured and unstructured data sources

Cloud Data Engineering

• Work extensively with AWS services including EMR, Redshift, S3, Glue, Lambda, Kinesis, and related data tools
• Build high-throughput, low-latency systems that support real-time or near-real-time decision making

Collaboration and Delivery

• Partner with data scientists, analysts, and engineering teams to deliver reliable and well-documented datasets
• Translate business requirements into technical specifications and scalable data solutions
• Mentor team members and contribute to best practices and reusable frameworks within Solvd

Automation and Continuous Improvement

• Streamline reporting, analytics, and data preparation processes
• Replace manual workflows with automated, repeatable systems
• Support ongoing performance tuning, monitoring, and platform optimization

Basic qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or similar
• 3 or more years of hands-on experience in data engineering or related fields
• Strong proficiency in SQL and data modeling for analytics and warehousing
• Experience building ETL or ELT pipelines at scale
• Experience with big data technologies such as Hadoop, Hive, Spark, HBase, or EMR
• Knowledge of distributed systems and data storage principles
• Basic scripting skills in Python or Scala
• Familiarity with machine learning concepts

Preferred qualifications

• Experience with AWS data services such as Redshift, S3, Glue, EMR, Kinesis, Firehose, and Lambda
• Experience working with non-relational data stores such as document, key-value, column-family, or graph databases
• Experience collaborating with cross-functional risk, compliance, or analytics teams
• Strong understanding of data governance, quality, and security best practices