S
Atlanta, GA(Onsite)
8 months + Extension
Senior Associate Technology L2
As a Senior Associate Technology L2 specializing in Data Platforms, you will play a key role in designing, developing, and optimizing data solutions that enable scalable, high-performance data processing. You will work with cutting-edge technologies to build robust data pipelines, data lakes, and analytics platforms that drive business insights and innovation.
Your Impact
- Design, develop, and maintain scalable data platforms that support enterprise data needs.
- Build and optimize data pipelines, ETL processes, and data integration workflows.
- Collaborate with data scientists, analysts, and business stakeholders to ensure data solutions meet business requirements.
- Implement best practices in data governance, security, and compliance.
- Work with cloud-based data platforms such as AWS, Azure, or Google Cloud Platform.
- Utilize big data technologies such as Hadoop, Spark, Kafka, and Snowflake.
- Automate data processing and monitoring using tools like Airflow, Kubernetes, or Apache NiFi.
- Troubleshoot and optimize data performance, ensuring high availability and reliability.
- Stay updated on emerging trends in data engineering and contribute to innovation within the team.
Skills & Experience
- 5+ years of experience in data engineering, data platforms, or related fields.
- Strong expertise in SQL, NoSQL, and data modeling.
- Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, or Snowflake.
- Proficiency in cloud-based data solutions (AWS, Azure, Google Cloud Platform).
- Experience with data pipeline orchestration tools like Apache Airflow, NiFi, or Kubernetes.
- Strong programming skills in Python, Java, Scala, or similar languages.
- Knowledge of data governance, security, and compliance best practices.
- Ability to work in an Agile environment and collaborate with cross-functional teams.
- Strong problem-solving and analytical skills with a focus on data-driven decision-making.
Set Yourself Apart With
- Experience with real-time data processing and streaming analytics.
- Knowledge of machine learning pipelines and data science workflows.
- Certifications in cloud platforms (AWS Certified Data Analytics Specialty, Azure Data Engineer, Google Cloud Platform Professional Data Engineer).
- Exposure to DevOps practices for data engineering.