Инженер данных

Solvd Inc. is an AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence.

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

• 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;
• Nice to have: 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.

• Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation;
• Be part of a global team with equal opportunities for collaboration across continents and cultures;
• Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.