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Job Title


Senior Data Engineer


Company : Kanerika Inc


Location : Hyderabad, Telangana


Created : 2025-12-18


Job Type : Full Time


Job Description

About The Role We are seeking a skilledData Engineerwith strong experience inDatabricks, Microsoft Fabric, or Snowflake , along withPower BI expertise , to design, build, and optimize scalable data pipelines and analytics solutions. You will also play a key role in enabling effective data visualization and reporting for business stakeholders.Key Responsibilities Design, develop, and maintainETL/ELT pipelinesusing Databricks, Fabric, or Snowflake. Build and optimizedata workflowsfor performance, scalability, and cost efficiency in cloud environments (Azure/AWS/GCP). Implement and managedata lakes, data warehouses, or lakehouse architectures . Develop and maintainPower BI dashboards and reportsto support business insights and decision-making. Collaborate with cross-functional teams to definedata requirements, governance standards, and best practices . Ensuredata quality, integrity, and securityacross all platforms. Automate workflows and supportCI/CD deploymentsfor data solutions. Monitor and troubleshoot pipelines and dashboards to ensure high availability and reliability.Required Qualifications Bachelor’s/Master’s degreein Computer Science, Information Technology, Engineering, or related field. 5-7 yearsof experience in Data Engineering. Proven experience as aData Engineerwith expertise inDatabricks OR Fabric OR Snowflake . Hands-on experience withPower BI(data modeling, DAX, dashboard creation, performance optimization). Strong proficiency inSQLand at least one programming language (Python/Scala/Java). Experience withdata modelingand building scalable pipelines in cloud environments. Knowledge ofAzure, AWS, or GCPand their data ecosystem. Strong problem-solving, analytical, and communication skills.Preferred Qualifications Experience withstreaming data technologies(Kafka, Event Hubs, Kinesis). Knowledge ofDelta Lake, Synapse, or Snowflake performance optimization . Familiarity withDevOps practicesfor data (CI/CD, Git, Infrastructure as Code). Exposure tomachine learning pipelinesor advanced analytics. Understanding ofdata governance, lineage, and compliance frameworks