Required Skills
* Programming & data processing: Advanced SQL and Python; plus Scala/Java for Spark/Flink. Go lang is a plus
* Cloud data platforms: Hands on with one or more among BigQuery, Snowflake, Redshift, Synapse/Databricks SQL; deep understanding of cloud DW vs traditional MPP trade offs.
* Data modelling: Dimensional (star/snowflake), Data Vault 2.0, SCD implementations, and schema versioning/evolution.
* Streaming: Kafka/Pub/Sub/Kinesis with Spark Structured Streaming or Flink; event schemas (Avro/Protobuf), idempotency, back pressure, replay.
* Orchestration & ELT: Airflow/Composer/Managed Workflows and/or dbt (or equivalents) for transformations, testing, and documentation.
* CI/CD & platform engineering: Git workflows (trunk/PR), automated build/test/deploy, artifact versioning, Terraform/CloudFormation, Docker/Kubernetes.
* Data quality & governance: Data contracts, testing frameworks (e.g., Great Expectations/dbt tests), catalogue/lineage tooling, access policies.
* BI & semantics: Experience shaping semantic layers, KPIs/metrics logic, and consumption models; familiarity with enterprise BI tools and metric stores.
* AI readiness: Understanding of feature engineering, data for ML/GenAI, knowledge graphs/ontologies, and patterns that enable future knowledge layers.
* Security & compliance: IAM design, encryption, key management, masking/tokenization, and auditability in regulated environments.
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