> Markdown version of [/jobs/ext/4185633-associate-principal-data-sciences](https://www.wearedevelopers.com/jobs/ext/4185633-associate-principal-data-sciences). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Principal - Data Sciences - **Company:** LTM Inc - **Location:** Tampa, FL, United States - **Salary:** $119,230.0 - $166,598.0 - **Contract:** Internship / Graduate position - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Microsoft Azure, Big Data, Cloud Storage, Code Review, Databases, Continuous Integration, Data Architecture, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Security, Data Warehousing, Relational Databases, DevOps, Distributed Systems, Apache Hadoop, Hadoop Distributed File System, Apache Hive, Python (Programming Language), Apache Oozie, Performance Tuning, Standard Sql, Cloudera, Unstructured Data, Data Processing, Apache Yarn, Azure Data Factory, Apache Spark, Git, Data Lakes, Pyspark, Information Technology, AWS Glue, Apache Kafka, Spark Streaming, Data Management, Azure Synapse Analytics, Software Version Control, Data Pipelines, Databricks - **Published:** October 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ddd9951b36d8294e ## About the Role Strong experience in Python and PySpark development Handson experience with Apache Spark Spark SQL DataFrames and Spark Streaming Strong knowledge of SQL and relational databases Experience with ETL development and data warehousing concepts Familiarity with Hadoop ecosystem technologies HDFS Hive Yarn Experience with version control systems such as Git Understanding of distributed computing concepts and performance tuning Knowledge of workflow orchestration tools such as Airflow Oozie or Azure Data Factory Strong analytical and problemsolving skills Preferred Skills Experience with cloud platforms AWS EMR Azure Databricks Azure Synapse GCP Dataproc Exposure to Delta Lake Iceberg or Lakehouse architectures Experience with Kafka or other realtime streaming solutions Knowledge of CICD pipelines and DevOps practices Understanding of data governance security and compliance requirements Qualifications Bachelors or Masters degree in Computer Science Information Technology Engineering or a related field 58 years of experience in Data Engineering or Big Data development Relevant certifications in Spark Databricks Azure AWS or GCP are an added advantage NicetoHave Technologies Databricks Azure Data Factory ADF Azure Synapse Analytics AWS Glue, 11 years of experience in Data Engineering 11 years of handson experience with PySpark development Experience designing and supporting enterprisescale data platforms Proven ability to optimize Spark applications for highvolume data processing Key Competencies Communication and stakeholder management Problemsolving and analytical thinking Team collaboration Attention to detail Ownership and accountability, This JD can be used for Data Engineer PySpark Senior PySpark Developer or PySpark Lead roles with minor modifications to experience and leadership expectations ## Description We are seeking a skilled PySpark Developer to design develop and optimize largescale data processing solutions using Apache Spark and Python The ideal candidate will have experience building ETL pipelines handling big data workloads and working with cloudbased data platforms to support analytics reporting and data engineering initiatives, Design develop and maintain scalable data pipelines using PySpark Build and optimize ETLELT processes for structured and unstructured data Process large datasets using Apache Spark in distributed environments Collaborate with business analysts data architects and data scientists to understand data requirements Integrate data from multiple sources including databases APIs and cloud storage Perform data cleansing transformation and validation activities Optimize Spark jobs for performance scalability and resource utilization Develop data quality checks and monitoring mechanisms Troubleshoot production issues and provide timely resolutions Implement best practices for coding testing deployment and documentation Work with cloud platforms such as AWS Azure or GCP for data engineering solutions Participate in code reviews and ensure adherence to development standards