Senior Data Engineer — Cloud-Native Data Migration Lead

Reach IT; Portugal; Presencial; EUR 90 000 - 120 000; Tempo integral

Descrição da oferta de emprego

Our nearshore expertise sets us apart. We specialize in on-demand, scalable teams, technical excellence, and operational reliability. By bridging the talent gap, we support organizations modernizing large-scale enterprise data platforms and cloud-native analytics ecosystems.

We are looking for a Senior Data Engineer | Cloudera/Snowflake Migration 🛡️

To join an international data modernization initiative focused on migrating large-scale Cloudera/Hadoop ecosystems into modern cloud-native data platforms using Snowflake, Databricks, and distributed processing technologies.

The project involves large-scale migration and transformation of enterprise data workloads, re-architecting Hive/Impala environments, modernizing ETL pipelines, migrating HDFS-based ecosystems, and building scalable cloud-native data platforms across AWS or GCP environments, with direct interaction with international stakeholders and client-facing activities.

Skills:

🎯 +5 years of experience in Data Engineering or Software Engineering;

🎯 Experience with Hadoop, Cloudera, Hive, Impala, HDFS, and distributed data ecosystems;

🎯 Proven hands-on experience migrating large-scale Cloudera (CDH/HDP) platforms to Snowflake or Databricks;

🎯 Python, SQL, Spark and PySpark in high-performance production environments;

🎯 Modernizing and refactoring legacy ETL processes into cloud-native architectures;

🎯 Snowflake or Databricks modern data platform environments;

🎯 Snowpipe, Streams, Tasks, Auto Loader, Delta Live Tables, Unity Catalog, CDC, Reverse ETL, and API integrations;

Your Responsibilities:

✅ Lead technical migrations of legacy Hadoop / Cloudera ecosystems into modern cloud-native data platforms;

✅ Re-architect Hive and Impala workloads into Snowflake or Databricks environments;

✅ Migrate and modernize HDFS-based enterprise data platforms and legacy ETL pipelines;

✅ Develop migration, transformation, validation, and automation logic using Python, SQL, Spark, and PySpark;

✅ Build and orchestrate scalable cloud-native data platforms from scratch;

✅ Implement integrations including CDC, Reverse ETL, API ingestion, and distributed data workflows;

✅ Resolve platform incompatibilities, performance bottlenecks, and modernization challenges across enterprise data ecosystems;

✅ Collaborate directly with technical teams, business stakeholders, and international clients throughout project delivery;

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