Job Title: Senior Data Engineer
Experience: 7+ Years
Location: Noida
Employment Type: Full-Time
About the Role
We are looking for an experienced Senior Data Engineer with 7+ years of hands-on experience in designing, developing, and optimizing enterprise-scale data platforms. The ideal candidate will have deep expertise in building high-performance data pipelines, cloud-native data architectures, and big data technologies. You will play a key role in architecting scalable data solutions, mentoring team members, and collaborating with cross-functional teams to enable data-driven decision-making.
Key Responsibilities
Design, develop, and maintain scalable, secure, and high-performance data pipelines for batch and real-time data processing.
Architect and implement robust ETL/ELT frameworks to integrate data from multiple internal and external sources.
Build and optimize enterprise-grade data models to support reporting, analytics, business intelligence, and machine learning initiatives.
Process large-scale structured, semi-structured, and unstructured datasets efficiently.
Lead data platform modernization initiatives using cloud-native technologies and best practices.
Optimize data processing performance, storage, and query execution for scalability and cost efficiency.
Ensure data quality, governance, security, and compliance across the data ecosystem.
Collaborate with Data Scientists, BI Developers, Product Managers, and Engineering teams to define and implement data solutions.
Design and implement data orchestration workflows using modern scheduling frameworks.
Mentor junior engineers, conduct code reviews, and establish engineering best practices.
Drive automation, monitoring, troubleshooting, and continuous improvement of data pipelines.
Create and maintain technical documentation, architecture diagrams, and operational runbooks.
Required Skills & Experience
7+ years of experience in Data Engineering, Big Data, or Data Platform development.
Expert-level proficiency in Advanced SQL for data transformation, optimization, and performance tuning.
Strong programming experience in Python for data engineering and automation.
Extensive hands-on experience with Apache Spark for distributed data processing.
Strong experience with Databricks for large-scale data engineering workloads.
Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
Experience implementing real-time data streaming solutions using Apache Kafka.
Strong understanding of Data Warehousing concepts, dimensional modeling, star/snowflake schemas, and data architecture.
Hands-on experience with BigQuery or Snowflake as enterprise cloud data warehouses.
Strong experience with Google Cloud Platform (GCP) data services, including:
BigQuery
Dataflow
Pub/Sub
Proficiency in Git and collaborative version control practices.
Strong understanding of data security, governance, and access control principles.
Experience designing scalable, resilient, and cost-effective cloud data solutions.
Good to Have
Experience with dbt (Data Build Tool).
Strong knowledge of the Hadoop ecosystem (Hive, HDFS, Yarn, etc.).
Experience with Azure Data Factory (ADF).
Hands-on experience with AWS Glue.
Knowledge of Terraform and Infrastructure as Code (IaC).
Experience with Data Governance and Metadata Management tools such as Collibra, Alation, Apache Atlas, or similar.
Exposure to CI/CD pipelines and DevOps practices for data engineering.