Data Engineer

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Job Description: Futuralis is looking for a seasoned Data Engineer to design, build, and optimize data pipelines and workflows that support critical business decisions. The ideal candidate will drive scalable data solutions, contribute to architectural decisions, and provide technical leadership across projects. This role requires a strong focus on data quality, reliability, and collaboration with cross-functional teams. A passion for mentoring and driving best practices in data engineering is highly valued. Required Qualifications/Skills: - 5+ years of programming with at least one software programming language experience (e.g. Java, Python). - 5+ years of programming with PySpark - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience. - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience. - 3+ years of experience leading the team and cross-team architecture and design (architecture, design patterns, reliability and scaling) of new and current systems. - Experience in building large-scale data ingestion, data processing, data modeling. Familiarity with different data architectures. - Experience with designing, coding, troubleshooting, and supporting high volume and low latency distributed systems. - Experience with CI/CD and Infrastructure-as-Code such as AWS CDK. Preferred Qualifications: - Experience with AWS services like MWAA, AWS Glue, Lambda, Dynamo DB, Spark - Experience with OLAP and OLTP technologies - Experience with Amazon Build Tools Nice to Have: - AWS certification (e.g., AWS Certified Solutions Architect, AWS Certified Developer) is a plus.

Keyword: Lead Management

SQL Java Scala AWS Glue ETL Pipeline Python Tableau Amazon Redshift