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Senior Data Engineer

Senior Data Engineer

Fusemachines

5 - 10 years

5 - 9 Lacs

pune

Posted:4 days ago| Platform:

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Skills Required

performance tuning product engineering gcp rdbms data modeling data processing data quality sdlc sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Are you an experienced Data Engineering professional with a passion for building scalable, reliable, and high-performance data systemsDo you have hands-on experience designing and optimizing end-to-end real-time and batch pipelines, and developing cloud-native data architectures using modern technologies such as AWS, GCP, Azure, Databricks, and Snowflake

We are looking for a Senior Data Engineer to architect, design, and implement scalable, high-performance data solutions. The ideal candidate will be an expert in at least one major cloud data ecosystem (AWS, Azure, GCP, Snowflake, or Databricks) and possess a deep understanding of the end-to-end data lifecycle, from ingestion to business intelligence.

Qualification Skill Set Requirements

Core Technical Competencies

Experience: 5+ years of hands-on data engineering experience in a production environment. Languages: Strong proficiency in Python, SQL (complex queries, performance tuning), and PySpark/Apache Spark. Data Modeling: Expert knowledge of data modeling (3NF, Star, Snowflake Schema) and Lakehouse/Warehouse architectures. ETL/ELT Orchestration: Proven experience building pipelines using tools like dbt, Airflow, Dagster, or native cloud orchestrators (Glue, Data Factory, Composer). Integrations: Experienced in integrating data from diverse sources: APIs, RDBMS/NoSQL databases, flat files, and streaming platforms (Kafka, Kinesis, Pub/Sub).

Cloud Platform Expertise (Specialization-Specific)

Candidates should demonstrate deep expertise in anyone of the following: Snowflake: SnowSQL, Streams, Tasks, Snowpark, and cost optimization. Databricks: Delta Lake, Unity Catalog, Delta Live Tables (DLT), and Spark optimization. GCP: BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Functions. Azure: Synapse Analytics, Data Factory, Azure Databricks, and Stream Analytics. AWS: Redshift, S3, Lake Formation, Glue, and Lambda.

Professional Practices

SDLC DevOps: Proficient in Git workflows, CI/CD pipelines (GitHub Actions, Azure DevOps, AWS CodePipeline), and IaC (Terraform/CloudFormation). Data Governance: Strong understanding of data quality, lineage, observability, security (RBAC, encryption), and compliance frameworks. Agile: Active experience in Agile/Scrum environments using Jira or Azure Boards. Mentorship: Ability to lead projects and provide technical guidance to junior/mid-level engineers.

Responsibilities

Architecture: Architect, design, and implement scalable, reliable data solutions and pipelines aligned with business analytics needs. Optimization: Manage and fine-tune cloud resources and workloads for maximum performance, reliability, and cost-efficiency. Data Transformation: Lead the development of ETL/ELT processes for both batch and real-time data processing. Collaboration: Partner with Product, Engineering, and Data Science teams to deliver effective, data-driven solutions. Governance Quality: Promote and enforce best practices in data governance, security, and data quality frameworks. Mentorship: Provide technical leadership and mentorship to the team, ensuring architecture quality and best practices. Documentation: Maintain comprehensive documentation of data architectures, configurations, and workflows.

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Senior Data Engineer