Data Engineer / Senior Data Engineer

Аналитика рынка

Стек

Бесплатно, после входа в кабинет.

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Описание

Essential (Must-Have)• Strong Python, PySpark and SQL capability, including distributed processing, complex transformations, query optimisation, debugging and automated testing.• Hands-on experience with Databricks, Apache Spark and Delta Lake for production-scale batch or streaming data engineering.• Hands-on AWS data engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS, Lambda, Step Functions, Event Bridge, CloudWatch, Redshift and MSK/Kinesis.• Experience designing lakehouse or data-lake architectures, including layered data patterns, dimensional or domain data modelling and reusable curated datasets.• Experience implementing incremental ingestion, change data capture, idempotency, late-arriving data handling, backfills, replay and recovery.• Experience implementing data quality, schema validation, reconciliation, metadata and lineage as automated parts of production pipelines.• Experience with workflow orchestration, Git-based development, CI/CD, infrastructure as code such as Terraform, and environment promotion controls.• Ability to implement pipeline observability, operational dashboards, alerting, runbooks, incident diagnosis and service recovery.• Working knowledge of cloud security, least-privilege access, network boundaries, encryption, secret management, data classification and audit logging.• Ability to review technical designs and code, establish engineering standards, and guide less-experienced engineers. Preferred (Advantageous)• Ex

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