Senior Engineer – Data Engineering, Databricks

Object Edge

. Serve as a technical leader on teams delivering innovative solutions on the Databricks Platform .

Posted 11/6/2026contractRemote • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing data platforms using the Databricks platform, with a strong focus on data pipeline design, implementation, and quality assurance. Proficient in leveraging modern data technologies and methodologies to deliver scalable and efficient data solutions.

Highest-signal resume keywords

Databricks Platform ExperienceData Pipeline Design and DevelopmentApache Spark ProficiencySQL Programming SkillsData Quality and Observability Solutions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData Pipeline DesignYAML ConfigurationBatch and Streaming Data ProcessingSQLJavaPythonPySparkApache SparkPresto

Tools & Technologies

DatabricksDelta LakeAirflowDbtAmazon RedshiftSnowflakeGoogle BigQueryTerraformMLflowGreat Expectations

Certifications & Qualifications

Databricks Data Engineering AssociateDatabricks Data Engineering Professional

Industry Keywords

Cloud Data LakehouseDistributed Processing EnginesEvent Streaming PlatformsData QualityPipeline AuditObservability SolutionsInfrastructure as CodeNoSQL DatabasesContainer Management SystemsAI/ML Workflows

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheBigQueryCloudJavaNoSQLPySparkPythonSnowflakeSparkSQLTerraformUnity

About the role

Key responsibilities & impact

Serve as a technical leader on teams delivering innovative solutions on the Databricks Platform
Build next-generation data platforms using cloud data lakehouse methodologies, distributed processing engines, event streaming platforms, and modern data technologies
Participate in the Databricks Center of Excellence
Work under a Solution Architect to design and implement components of clients’ data platform solutions
Participate in design sessions, break down complex development tasks, and complete development items on time
Contribute to Center of Excellence initiatives by developing Databricks solution accelerators
Develop and implement data solutions using Databricks
Collaborate with cross-functional teams to design and optimize batch and streaming data pipelines while ensuring data quality and efficiency
Stay current with emerging technologies and Databricks platform features and continuously improve relevant skills

Requirements

What you’ll need

5+ years of data engineering experience, with at least 2 years of hands-on data pipeline design and development experience with Databricks
Experience with Databricks platform features including Delta Lake, Uniform (Iceberg), Delta Live Tables (Lakeflow Declarative Pipelines), and Unity Catalog
Proficiency in designing and building robust, scalable, YAML configuration driven data pipelines with batch, micro-batch, and streaming data ingestion and processing patterns using tools like Auto Loader
Experience building complex job/workflow orchestration patterns using Databricks jobs/workflows or tools such as Airflow and dbt
Exposure to data quality, pipeline audit, and observability solutions using Databricks native features or tools/frameworks such as Great Expectations, Collibra, and dbt
Proficiency in Apache Spark, Presto, and Amazon EMR
Experience with Amazon Redshift, Snowflake, and Google BigQuery
Strong programming skills using SQL, stored procedures, and object-oriented programming languages such as Java, Python, and PySpark
Familiarity with DevOps and CI/CD pipelines using Databricks Asset Bundles with automated validation and testing
Exposure to Infrastructure as Code tools such as Terraform is a big plus
Familiarity with NoSQL databases and container management systems
Exposure to AI/ML tools such as MLflow, prompt engineering, and modern data and AI agentic workflows
Databricks Data Engineering Associate and/or Professional certification is ideal, not explicitly required
Multiple Databricks project delivery experience is ideal