InfoSpeed Services, Inc.
Website:
infospeedinc.com
Job details:
Senior Data Engineer
Key Responsibilities
• Lead the design, development, and maintenance of scalable, high-performance data pipelines and data architectures to support analytics, AI/ML, and reporting requirements.
• Integrate data from multiple sources while ensuring data quality, consistency, accuracy, and governance across platforms.
• Design, implement, and optimize complex data models using Spark and other big data technologies to support analytical and business use cases.
• Write and optimize efficient SQL and Python code for data extraction, transformation, automation, and large-scale data processing.
• Work with big data and distributed processing technologies such as Apache Spark, Kafka, and Delta Lake.
• Design and implement cloud-based data solutions on platforms such as Azure, AWS, or GCP using services like Databricks, Synapse, Snowflake, or BigQuery.
• Identify performance bottlenecks and optimize data workflows for scalability, speed, reliability, and cost efficiency.
• Collaborate with data scientists, analysts, business stakeholders, and cross-functional teams to understand data requirements and deliver effective solutions.
• Mentor junior engineers, promote engineering best practices, and contribute to technical excellence within the data team.
• Stay updated with emerging trends in data engineering and proactively recommend improvements for future-ready data platforms.
Required Skills and Qualifications
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• 5–7 years of experience in data engineering or a related role, with proven experience in handling complex data projects.
• Strong proficiency in Python, including automation, scripting, and data manipulation.
• Deep knowledge of Apache Spark and distributed data processing frameworks.
• Advanced SQL skills with experience in writing and optimizing complex queries.
• Strong experience in data modelling, data architecture, and designing scalable enterprise-level data solutions.
• Hands-on experience with at least one major cloud platform such as Azure, AWS, or GCP.
• Good understanding of data warehousing, ETL/ELT, data governance, and modern data management practices.
• Strong analytical and troubleshooting skills to resolve data-related issues in large-scale environments.
• Excellent communication skills with experience collaborating with stakeholders and technical teams.
• Experience in leading technical teams or mentoring junior engineers.
Preferred Qualifications
• Strong experience with Databricks and Delta Lake.
• Relevant certifications such as Azure Data Engineer Associate, AWS Big Data Specialty, GCP Professional Data Engineer, or Databricks certifications.
• Exposure to Data Mesh, Data Fabric, or enterprise-scale data architecture patterns.
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