Data Engineer

Data Engineer
Duration : Long term
Location : Sacramento, CA

Mandatory Qualifications:

1) Must have a minimum of eight (8) years of experience in designing scalable ETL/ELT workflows using tools like Informatics, Apache Airflow, Databricks SSIS, Azure Data Factory or dbt.
2)Must have a minimum of six (6) years of experience of building and managing data pipelines in AWS (Glue, Redshift), Azure (ADF, Synapse), Google Cloud Platform (Dataflow, BigQuery) or hybrid environments using Spark, Kafka, Flink, or Kinesis with knowledge of optimizing for scale and latency.
3) Must have a minimum of six (6) years of experience of data modeling techniques (e.g., Star, Snowflake, Data Vault) and data warehouse architecture in both traditional and cloud-native environments.
4) Must have a minimum of five (5) years of experience in Python, SQL and optionally Scala or Java for building data transformations, automation and custom pipeline components.
5) Must have a minimum of five (5) years of experience implementing data quality validation, anomaly detection, and pipeline monitoring and observability using tools such as Informatica Data Quality (DQ), Anomalo, Soda SQL, Datafold, or other custom frameworks
6) Must have a minimum of five (5) years of experience in metadata management, data lineage, and catalog tools such as Informatica EDC, Alation, Collibra or OpenMetadata.
7) Must have a minimum of five (5) years of experience in CI/CD for data workflows, version control (Git), containerization (Docker), and IaC tools such as Terraform, Ansible or CloudFormation
8) Must have a minimum of five (5) years of experience in data encryption, access control, and regulatory compliance standards such as GDPR, HIPAA or SOC 2 and working in cross-functional agile teams with strong communication skills for collaborating with architects, analysts, and business stakeholders

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