Data Engineer

VAK Consulting LLC

6 - 11 years

10 - 18 Lacs

hyderabad

Posted:2 hours ago| Platform:

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Skills Required

python s3 rds glue ec2 lambada aws grafana lambda redshift sql

Work Mode

Work from Office

Job Type

Full Time

Job Description

Responsibilities

Design, develop, and maintain scalable and efficient data pipelines using Python and AWS technologies e.g. Lambda, EC2, S3, RDS, Redshift, Glue.
Architect and optimize data models and data processing algorithms to meet business requirements.
Implement and manage logging and monitoring solutions; create dashboards for tracking data flows and system health.
Work with both structured and unstructured data, ensuring accuracy and consistency across data platforms.
Translate business requirements to technical terms to translate business requirements into technical solutions.
Provide expertise in data governance, including metadata design, review, testing, monitoring, and documentation.
Provide team support and mentoring, fostering a culture of knowledge sharing and technical excellence.
Participate in code reviews and technical skill development.
Remain current on emerging data technologies and recommend improvements to our data architecture.

Qualifications

Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or related field.
5+ years experience in Python programming with strong emphasis on data engineering.
Strong experience with AWS services relevant for data engineering and analytics.
Experience in building reliable and scalable systems for high performance data processing.
Deep expertise working with Linux-based environments.
Deep technical experience with modern database technologies and distributed systems.
Strong proficiency with SQL (relational databases) and NoSQL (data warehousing, data lakes, and related).
Database, monitoring, logging, and infrastructure tooling CloudWatch, Grafana.
Excellent problem-solving and communication skills.

Preferred Skills:

Experience with big data tools and stream processing frameworks.
Knowledge of DevOps processes in a data engineering context.
Exposure to machine learning operations and integration with ML models if data engineering role overlaps with AI/ML.
Familiarity with containerization (Docker/Kubernetes) and workflow orchestration.

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