Azure Data Engineer (Trifacta/Adverity/Alteryx/Python)

Dentsu Global Services; Bengaluru; Presencial; INR 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Dentsu Global Services in Bengaluru is seeking a seasoned Data Engineer to architect and operate scalable data pipelines across marketing, media, and platform sources. You will implement Adverity-based ingestion, model DSP data with CM360 alignment, and maintain governed data in Databricks.

You will design reusable data models, ensure data quality with automated checks, and collaborate across teams to enable analytics, reporting, and AI-ready datasets using SQL, Python, and PySpark.

Formación

• 4-6+ years of experience as a Data Engineer or in a similar role building and operating scalable, production data pipelines.
• Bachelor’s Degree in Computer Science, Engineering, Information Systems, or a related field required; Graduate degree preferred.
• Hands-on experience with Adverity for data onboarding and normalization, including building and maintaining Data Refinery ingestion pipelines across multiple marketing and media sources.
• Proven experience managing data transformations in Trifacta (Alteryx Designer Cloud), including building governed, repeatable wrangling recipes for cleansing and standardization.
• Advanced expertise with Databricks, including Unity Catalog governance (catalogs, permissions, lineage, metadata), transformation development in SQL and PySpark, and Databricks Workflows, Notebooks, and Jobs.
• Demonstrated experience designing and operating data quality health checks, including integrity tests, reconciliation logic, schema validation, and automated monitoring, within a Databricks environment.
• Familiarity with dbt (dbt Labs) for transformation orchestration and testing, and with GitHub for version control, CI/CD, and code governance in a collaborative development workflow.
• Strong proficiency in SQL and Python for data engineering, transformation, and automation.
• Working knowledge of medallion (bronze/silver/gold) architecture, data modeling, lineage, and governance best practices for analytics-ready data.
• Self-starter with the ability to learn new tools quickly and deliver scalable, well-documented solutions across the data stack, driving continuous improvement and measurable impact.
• Bonus: Experience in advertising, marketing, or digital media environments, particularly performance reporting, reconciliation automation, or data quality optimization.

Responsabilidades

• Onboard and normalize multi-source data through Adverity, standing up and maintaining Data Refinery pipelines that connect marketing, media, and platform sources into a single, reliable ingestion layer.
• Ingest, model, and reconcile DSP data against CM360 ad-server delivery, applying programmatic media expertise to distinguish buy-side activation and bidding from independent ad serving/counting, and to resolve discrepancies between platforms.
• Manage and maintain data transformations in Trifacta, building governed, repeatable wrangling recipes that cleanse, standardize, and shape raw inputs into analytics-ready structures.
• Govern data assets in Databricks Unity Catalog, managing catalogs, schemas, permissions, lineage, and metadata to keep data secure, consistent, and discoverable across the platform.
• Develop and optimize further transformations in Databricks using SQL, PySpark, notebooks, and workflows, extending refined data through the medallion architecture into curated, consumption-ready models.
• Design, run, and monitor data quality health checks in Databricks, including row-level integrity, schema and version validation, reconciliation logic, and automated error logging, to embed trust and observability at every stage of the pipeline.
• Collaborate with analysts, engineers, and business leads to translate raw, multi-source data into governed, insight-ready datasets that support performance reporting and downstream decisioning.
• Prepare certified, well-modeled datasets for the consumption layer and reporting tools such as Power BI, ensuring metrics are consistent, governed, and traceable to source.

Conocimientos

Data engineering

SQL

Python

Databricks

Unity Catalog

dbt

GitHub

PySpark

Trifacta

Adverity

Power BI

Educación

Bachelor’s degree in Computer Science/Engineering/Information Systems

Graduate degree preferred

Herramientas

Databricks Unity Catalog

Trifacta

dbt

GitHub

Power BI

PySpark

Descripción del empleo

• Onboard and normalize multi-source data through Adverity, standing up and maintaining Data Refinery pipelines that connect marketing, media, and platform sources into a single, reliable ingestion layer.
• Ingest, model, and reconcile DSP data (e.g., DV360, The Trade Desk, Amazon DSP) against CM360 ad-server delivery, applying programmatic media expertise to distinguish buy-side activation and bidding from independent ad serving/counting, and to resolve impression, spend, and attribution discrepancies between platforms.
• Manage and maintain data transformations in Trifacta, building governed, repeatable wrangling recipes that cleanse, standardize, and shape raw inputs into analytics-ready structures.
• Govern data assets in Databricks Unity Catalog, managing catalogs, schemas, permissions, lineage, and metadata to keep data secure, consistent, and discoverable across the platform.
• Develop and optimize further transformations in Databricks using SQL, PySpark, notebooks, and workflows, extending refined data through the medallion (bronze/silver/gold) architecture into curated, consumption-ready models.
• Design, run, and monitor data quality health checks in Databricks, including row-level integrity, schema and version validation, reconciliation logic, and automated error logging, to embed trust and observability at every stage of the pipeline.
• Working understanding and familiarity to apply modular, tested, and documented transformation orchestration, and GitHub for version control, CI/CD, code review, and change governance across SQL, Python, and YAML assets.
• Design modular, reusable, and well-documented data models that support analytics, reporting, and AI enablement, with clear definitions, lineage, and business context.
• Collaborate with analysts, engineers, and business leads to translate raw, multi-source data into governed, insight-ready datasets that support performance reporting and downstream decisioning.
• Contribute to data quality standards, monitoring, and the platform roadmap, defining best practices for reusable components, transformation patterns, and observability that scale across teams and clients.
• Prepare certified, well-modeled datasets for the consumption layer and reporting tools such as Power BI, ensuring metrics are consistent, governed, and traceable to source.

Required Qualifications

• 4-6+ years of experience as a Data Engineer or in a similar role building and operating scalable, production data pipelines.
• Bachelor’s Degree in Computer Science, Engineering, Information Systems, or a related field required; Graduate degree preferred.
• Hands-on experience with Adverity for data onboarding and normalization, including building and maintaining Data Refinery ingestion pipelines across multiple marketing and media sources.
• Proven experience managing data transformations in Trifacta (Alteryx Designer Cloud), including building governed, repeatable wrangling recipes for cleansing and standardization.
• Advanced expertise with Databricks, including Unity Catalog governance (catalogs, permissions, lineage, metadata), transformation development in SQL and PySpark, and Databricks Workflows, Notebooks, and Jobs.
• Demonstrated experience designing and operating data quality health checks, including integrity tests, reconciliation logic, schema validation, and automated monitoring, within a Databricks environment.
• Familiarity with dbt (dbt Labs) for transformation orchestration and testing, and with GitHub for version control, CI/CD, and code governance in a collaborative development workflow.
• Strong proficiency in SQL and Python for data engineering, transformation, and automation.
• Working knowledge of medallion (bronze/silver/gold) architecture, data modeling, lineage, and governance best practices for analytics-ready data.
• Self-starter with the ability to learn new tools quickly and deliver scalable, well-documented solutions across the data stack, driving continuous improvement and measurable impact.
• Bonus: Experience in advertising, marketing, or digital media environments, particularly performance reporting, reconciliation automation, or data quality optimization.