Staffbee Solutions INC | Senior Data Engineer
10 hours ago
Looking for Freelance Opportunity In Data engineering?
We are seeking the Data Engineer Panelist @ 8+ years of Experience
This Is a Freelace_WFH/Remote_USA Shift Opportunity
Must have atleast 8+ Years of exp at any one One cloud Tech @ GCP, AZure or AWS
should have excellent knowledge @ Hadoop, python/pyspark, Bigdata,SQL & ETL
Role Overview:
We are seeking a highly experienced Data Engineer to serve as a panelist for evaluating candidates in technical interviews. This role requires a deep understanding of advanced data engineering technologies and practices, along with strong assessment capabilities.
Key Responsibilities:
- Conduct technical interviews to evaluate candidates expertise in Data Engineering.
- Provide detailed feedback on candidates’ performance and technical proficiency.
- Collaborate with the hiring team to refine interview processes and evaluation criteria.
Qualifications:
Mandatory Technical Expertise:
- Cloud Platforms: Advanced knowledge in at least one cloud platform (GCP, Azure, AWS), including services like BigQuery, Azure Synapse, or AWS Redshift.
- Big Data Frameworks: Expertise in Hadoop ecosystem components (HDFS, YARN, Hive, HBase), and Spark (including PySpark).
- Programming: Proficiency in Python (including libraries like Pandas, NumPy, and PyArrow) and Scala.
- ETL Processes: Extensive experience in designing and implementing complex ETL pipelines using tools like Apache NiFi, Airflow, or Informatica.
- Data Modeling: Strong skills in data modeling for both structured and unstructured data, including dimensional modeling and schema design.
- SQL Expertise: Advanced knowledge of SQL, query optimization, and handling large-scale relational databases (e.g., PostgreSQL, MySQL, or Snowflake).
- Data Storage & Processing: Familiarity with NoSQL databases (e.g., Cassandra, MongoDB) and distributed data processing techniques.
- DevOps for Data Engineering: Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and Infrastructure as Code (e.g., Terraform).
- Security: Knowledge of data security protocols, encryption methods, and compliance standards like GDPR or HIPAA.
Additional Skills:
- Experience with real-time data processing frameworks like Kafka, Flink, or Storm.
- Hands-on knowledge of machine learning pipelines and MLOps tools like MLflow.
- Familiarity with data governance and cataloging tools like Apache Atlas or Collibra.
Soft Skills:
- Exceptional communication and interpersonal skills to effectively engage with candidates.
- Proven ability to assess technical knowledge accurately and provide constructive feedback.
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