We are looking for an experienced Senior Data Engineer who will lead the design and development of modern data platforms and scalable data pipelines. The ideal candidate has strong hands-on expertise in cloud data engineering, big data technologies, ELT/ETL architecture, and data modeling, along with the ability to mentor teams and work closely with business stakeholders to deliver high-quality data solutions.
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Architect, design, and implement large-scale data pipelines and data integration workflows across structured and unstructured datasets.
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Build, optimize, and maintain robust ETL/ELT processes for ingestion, transformation, and delivery of data across enterprise systems.
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Develop and manage data lakes, data warehouses, and analytics platforms using cloud technologies.
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Work closely with data scientists, analysts, and business teams to understand data requirements and deliver reliable data for reporting and analytics.
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Define best practices for data quality, lineage, governance, security, and performance optimization.
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Lead and mentor junior engineers, participate in design/code reviews, and ensure engineering excellence.
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Collaborate with cross-functional teams in an Agile environment for solution design and implementation.
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Own production deployment, monitoring, debugging, performance tuning, and incident management for data pipelines.
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12+ years of experience in Data Engineering, Data Architecture, or similar roles.
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Strong programming skills in Python / Java / Scala.
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Expert in SQL and performance tuning for large datasets.
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Hands-on experience with Big Data ecosystems Hadoop, Spark, Kafka, Hive, HBase, etc.
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Strong experience with Cloud platforms (AWS / Azure / GCP) and services like:
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AWS: S3, Glue, EMR, Redshift, Lambda, Kinesis
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Azure: Data Factory, Synapse, Databricks, ADLS
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GCP: BigQuery, Dataflow, Pub/Sub
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Experience with Data Warehouse / Data Lake / Lakehouse design and modeling (Kimball, OLAP, OLTP, Star/Snowflake schemas).
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Proficiency in CI/CD, Git, Docker, Kubernetes, Airflow or similar orchestration tools.
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Knowledge of data governance, security, metadata management, and data quality frameworks.