Role Overview

We are looking for a

Data Engineer to design, build, and maintain scalable data systems and infrastructure. In this role, you will collaborate with cross-functional teams to gather requirements, develop data pipelines, and implement best practices for data governance, security, and analytics. This position offers the opportunity to shape a core part of our data environment and directly influence how we leverage data for business insights and innovation.

Key Responsibilities

- Architect and Implement Data Solutions

- Design and build scalable data platforms using [AWS, Azure, or GCP] or on-premises technologies.

- Develop best practices for data storage, ingestion, and processing (batch and streaming).

- Data Pipeline Development

- Create and manage robust ETL/ELT workflows handling various data types (structured, semi-structured, unstructured).

- Optimize data pipelines for reliability, scalability, and performance.

- Data Governance and Security

- Define and enforce governance policies including data retention, cataloging, and lineage tracking.

- Ensure compliance with relevant data privacy regulations (GDPR, CCPA, HIPAA, etc.) through appropriate security controls and encryption.

- Metadata Management and Cataloging

- Implement and maintain data catalog solutions (e.g., AWS Glue, Apache Atlas, Collibra, or Alation).

- Automate the detection of recent data sets, schema changes, and lineage updates.

- Data Quality and Monitoring

- Establish automated checks and alerts for data quality, completeness, and consistency.

- Troubleshoot and resolve data-related issues, providing root cause analysis and long-term fixes.

- Collaboration and Mentorship





- Work closely with cross-functional stakeholders to translate requirements into scalable technical solutions.

Qualifications

- Education & Experience

- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; or equivalent experience.

- 4+ years of hands-on experience in data engineering, data infrastructure, or related fields.

- Technical Skills

- Proven experience with cloud platforms (AWS, Azure, or GCP) and object storage (S3, ADLS, GCS).

- Proficiency in distributed data processing tools like Apache Spark or Databricks.

- Strong SQL skills and experience with one or more programming languages (Python, Scala, Java).

- Familiarity with real-time data streaming solutions (Kafka, Kinesis, etc.).

- Knowledge of data modeling and modern data architecture patterns.

- Data Governance & Security

- Track record of implementing data catalog and lineage solutions.

- Experience with data quality frameworks (e.g., Great Expectations, Deequ) is a plus.

- Understanding of RBAC, ABAC, encryption, and other security best practices.

- Soft Skills

- Excellent communication and stakeholder management skills.

- Ability to explain complex technical concepts to both technical and non-technical audiences.

- Experience in agile methodologies and cross-functional collaboration.

Nice-to-Have

- Certifications in AWS, Azure, or GCP (e.g., AWS Certified Data Analytics – Specialty, Azure Data Engineer).

- Experience with infrastructure-as-code (Terraform, CloudFormation).

- Familiarity with orchestration tools like Airflow, Luigi, or Dagster.

- Experience with containerization and CI/CD for data engineering pipelines.

📌 Data Engineer (Surat)
🏢 Anand Systems
📍 Surat