Data Engineering Lead

Job Summary:

We are seeking a highly skilled Lead Data Engineer to join our dynamic team. The ideal candidate will possess a strong background in data engineering, with a focus on designing and implementing robust data solutions. This role requires expertise in AWS, PySpark, and Apache Flink for real-time streaming applications. The Lead Data Engineer will be responsible for architecting data solutions that meet business needs while ensuring scalability, reliability, and performance.

Responsibilities:

• Design and implement data pipelines and architectures to support real-time data processing and analytics.
• Collaborate with cross-functional teams to gather requirements and translate them into technical specifications.
• Lead the development and optimization of data models, ETL processes, and data integration workflows.
• Utilize AWS services to build and maintain scalable data solutions.
• Implement best practices for data governance, security, and compliance.
• Mentor and guide junior data engineers in technical skills and project methodologies.
• Stay updated with industry trends and emerging technologies to continuously improve data engineering practices.
• Conduct performance tuning and optimization of data processing jobs.
• Ensure high availability and reliability of data systems through proactive monitoring and maintenance.

Mandatory Skills:

• Proficiency in AWS services, including but not limited to S3, Redshift, Lambda, and Glue.
• Strong experience with PySpark for large-scale data processing.
• Hands-on experience with Apache Flink for real-time data streaming.
• Expertise in data architecture and design principles.
• Proven ability to develop and implement data solutions in a cloud environment.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
• Deal breaker skill: Proficiency in Databricks.

Preferred Skills:

• Experience with data warehousing solutions and data lakes.
• Familiarity with machine learning frameworks and tools.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Experience with CI/CD pipelines and DevOps practices.
• Understanding of data visualization tools and techniques.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Relevant certifications in data engineering or cloud technologies are a plus.
• Demonstrated ability to lead projects and work effectively in a team-oriented environment.

If you are passionate about data engineering and want to make a significant impact in a fast-paced environment, we encourage you to apply for this exciting opportunity.

About Mphasis:

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis Front2Back Transformation approach. Front2Back uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2TM=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.