Senior Data Engineer - Cloud Platform (10-15 yrs)

We are seeking the Data Engineer Panelist @ 10+ years of Experience

This Is a Freelance_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.