Pyspark data engineer

???? Contract Assistant – Data Engineer Support (Remote, EST Hours) ???????? Start Date: Sept 10, 2025⏳ Duration: 6 months (extendable)???? Pay: $1,000/month???? Work Hours: 8:00 AM – 5:30 PM ESTWe’re looking for a Contract Assistant to support a Py Spark Data Engineer with daily activities. This is a remote contract role (not formal employment).What You’ll Do:Execute creative software and data solutions, including design, development, and technical troubleshooting, by thinking beyond routine approaches to build solutions or break down technical problems.Develop secure, high-quality production code and data pipelines, reviewing and debugging processes implemented by others.Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability of software applications and systems.Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs and technical credentials.Work with business stakeholders to understand requirements and design appropriate solutions, producing architecture and design artifacts for complex applications.Implement robust monitoring and alerting systems to proactively identify and address data ingestion issues, optimizing performance and throughput.Implement data quality checks and validation processes to ensure accuracy and reliability of data.Design and implement scalable data frameworks to manage end-to-end data pipelines for workforce data analytics.Share and develop best practices with Platform and Architecture teams to improve data pipeline framework and modernize the workforce data analytics platform.Gather, analyze, and synthesize large, diverse data sets to continuously improve capabilities and user experiences, leveraging data-driven insights.Contribute to software engineering communities of practice and events that explore new and emerging technologies, fostering a culture of diversity, opportunity, inclusion, and respect.What You’ll Need:Ability to work alongside me during US EST business hours.5+ years of applied experience in data engineering, including design, application development, testing, and operational stability.Advanced proficiency in data processing frameworks and tools, including Parquet, Iceberg, Py Spark, Glue, Lambda, Databricks, and AWS data services like EMR, Athena, and Redshift.Proficiency in programming languages like Python, Java, or Scala for data processing and application development.Proficiency in automation and continuous delivery methods, utilizing CI/CD pipelines with tools like Git/Bitbucket, Jenkins, or Spinnaker for automated deployment and version control.Hands-on practical experience delivering system design, application development, testing, and operational stability, with advanced understanding of agile methodologies, application resiliency, and security.Demonstrated proficiency in software applications and technical processes within technical disciplines like cloud, artificial intelligence, machine learning, and mobile.In-depth knowledge of the financial services industry and their IT systems.Proficiency in database management and data modeling, working with relational databases like Oracle or SQL Server. Skilled in writing SQL queries for efficient data management and retrieval, utilizing SQL tools such as DML for data handling, DDL for schema management, and PL/SQL for procedural extensions in Oracle databases.Experience with scheduling tools like Autosys to automate and manage job scheduling for efficient workflow execution.???? This role offers hands-on exposure to real-world BA activities, stakeholder engagement, and technology evaluation — perfect for someone looking to strengthen their BA career while working remotely.???? Interested? Send me a DM or comment below#Now Hiring #Remote Jobs #Tech Talent #Data Engineer #Hiring Now #Work From Home #Tech Opportunities #Job Alert #Py Spark #AWSData #Databricks #Glue #Lambda #EMR #Athena #Redshift #SQL #PLSQL #Python #Scala #Java #Automation #CICD #Jenkins #Bitbucket #Data Pipelines #Data Quality #Data Architecture