Job Description:
Pay Range: $07hr - $75hr
Responsibilities:
• Data Pipeline Development: Design, build, and maintain scalable data pipelines to ingest, process, and transform structured and unstructured data.
• Data Modeling: Create optimized data models to support analytics, reporting, and machine learning workflows.
• ETL/ELT Processes: Develop and manage ETL/ELT workflows to ensure clean, reliable, and high-quality data.
• Database Management: Work with relational and NoSQL databases to ensure efficient storage and retrieval of large datasets.
• Cloud Data Solutions: Implement and optimize data solutions on cloud platforms like AWS, Azure, or GCP.
• Data Quality & Governance: Ensure data integrity, security, compliance, and quality across systems.
• Collaboration: Partner with data scientists, analysts, and software engineers to deliver reliable data infrastructure.
• utomation: Streamline data processes using orchestration tools and automation frameworks.
• Monitoring & Optimization: Implement monitoring, logging, and performance tuning of data systems.
• Documentation: Maintain detailed documentation of data pipelines, architecture, and workflows.
Skills:
• Programming Skills: Proficiency in Python, SQL, and familiarity with Java/Scala.
• Data Pipelines & ETL: Experience with ETL tools (Airflow, DBT, Informatica, Talend).
• Big Data Frameworks: Knowledge of Spark, Hadoop, Kafka, or Flink.
• Data Warehousing: Hands-on experience with Snowflake, Redshift, BigQuery, or Synapse.
• Cloud Platforms: Proficiency in AWS (Glue, Redshift, S3), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow).
• Databases: Strong experience with relational databases (PostgreSQL, MySQL, Oracle) and NoSQL databases (MongoDB, Cassandra).
• Data Modeling: Expertise in designing star/snowflake schemas, OLTP/OLAP systems.
• DevOps & Version Control: Familiarity with Git, CI/CD pipelines, and Infrastructure as Code (Terraform).
• Data Governance & Security: Knowledge of GDPR, HIPAA, encryption, role-based access controls.
• nalytical Skills: Strong problem-solving and optimization skills in handling big data.
• Collaboration & Communication: Ability to work in cross-functional teams and clearly document technical processes.
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