Key Responsibilities & Required Skills:
Design, build, and maintain data pipelines and ETL workflows for data ingestion, transformation, and integration.
Develop scalable and efficient data processing solutions using Python, Java, or Scala .
Work with big data frameworks such as Apache Spark, Hadoop, Kafka, Beam, or Flink for large-scale data processing.
Build and manage data warehouse and lakehouse solutions using Snowflake, Databricks, Redshift, or BigQuery .
Implement data quality, validation, and monitoring processes to ensure the accuracy and reliability of data.
Optimize data storage and processing for performance, scalability, and cost-efficiency .
Work closely with data analysts, data scientists, and business stakeholders to provide clean, structured, and reliable data.
Manage data orchestration workflows using tools such as Apache Airflow, DBT, or NiFi .
Design and manage data models, schemas, and metadata to support analytical and operational workloads.
Develop CI/CD pipelines for automated data deployment and version control using Git, Jenkins, or Azure DevOps .
Work within cloud-native environments (AWS, Azure, or GCP) using services such as Lambda, Glue, Dataflow, or Data Factory .
Collaborate with architects to define data governance, security, and compliance best practices.
Document data flows, architecture, and technical specifications clearly and accurately.
Required Qualifications:
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
Proficiency in SQL and experience working with relational databases (PostgreSQL, MySQL, SQL Server, Oracle).
Hands-on experience with Python, Java, or Scala for data processing and automation.
Strong understanding of ETL principles, data modeling, and data architecture .
Experience with data integration tools (Informatica, Talend, AWS Glue, or Fivetran).
Exposure to containerization and orchestration tools such as Docker, Kubernetes, or OpenShift .
Familiarity with data versioning, testing, and observability practices.
Experience working in Agile environments with cross-functional teams.
Excellent analytical, troubleshooting, and problem-solving skills.
Relevant certifications such as AWS Certified Data Engineer, Azure Data Engineer Associate, or Google Data Engineer are a plus.
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