Job Summary:

We are looking for a highly skilled and experienced Senior Data Engineer with 8+ years of expertise in designing, building, and optimizing large-scale data pipelines, data warehouses, and data platforms. The ideal candidate will have strong experience in data modeling, ETL/ELT processes, cloud-based data solutions, and big data technologies. This role requires close collaboration with data scientists, analysts, and business stakeholders to ensure reliable, scalable, and high-performance data solutions.

Key Responsibilities:

Design, develop, and maintain scalable and reliable data pipelines for batch and real-time data processing.
Build and optimize data warehouses, data lakes, and data marts to support analytics and reporting needs.
Develop and maintain ETL/ELT processes for ingesting, transforming, and integrating data from multiple sources.
Implement data quality, governance, and security standards across all data platforms.
Collaborate with data scientists and analysts to ensure accessibility and usability of datasets.
Optimize data pipelines for performance, scalability, and cost efficiency.
Work with cloud-based platforms (AWS, Azure, GCP) for data storage and processing.
Monitor, troubleshoot, and improve data workflows and systems proactively.
Mentor junior data engineers and contribute to best practices and coding standards.
Partner with business stakeholders to understand data needs and translate them into technical solutions.

Required Skills & Qualifications:

8+ years of experience in data engineering, big data, or related fields.
Strong programming skills in Python, Java, or Scala.
Expertise with SQL and database technologies (RDBMS, NoSQL).
Hands-on experience with big data frameworks (Spark, Hadoop, Kafka, Flink).
Experience in ETL/ELT design and development using tools like Apache Airflow, Talend, Informatica, or dbt.
Proficiency with cloud platforms (AWS Redshift, Azure Synapse, GCP BigQuery, Snowflake, or Databricks).
Solid understanding of data modeling (dimensional & relational) and data architecture.
Familiarity with containerization and orchestration (Docker, Kubernetes).
Strong knowledge of CI/CD pipelines, Git, and DevOps practices for data solutions.
Excellent problem-solving and analytical skills with strong attention to detail.

Preferred Qualifications:

Experience with machine learning data pipelines and MLOps.
Knowledge of real-time data streaming and event-driven architectures.
Familiarity with data security and compliance frameworks (GDPR, HIPAA, etc.).
Certifications in AWS, Azure, or GCP data engineering.

Valzo Soft Solutions

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