Description

Senior Data Engineer — Marketing Operations

About The Role

As a Senior Data Engineer on the Marketing Operations team, you'll work cross-functionally with business domain experts, analytics, and engineering teams to design and implement our Data Warehouse model. You'll partner with the Business Analytics Data Engineering function to build a data foundation and processes that scale with company growth — architecting, designing, and implementing data pipelines that deliver insights from Product and Corporate Systems to key partners, data scientists, and decision-makers across Sales, Customer Success, Marketing, and Finance at Slack.

This role suits problem solvers who anticipate issues before they surface and look beyond immediate fixes. We're looking for self-starters who take pride in their craft, are detail- and quality-oriented, and are passionate about making a real impact at Slack.

Responsibilities

- Design, implement, and build pipelines that deliver data with measurable quality under SLA.
- Assemble complex, large data sets that meet functional requirements.
- Partner with data architects, domain experts, data analysts, and other teams to build trusted, well-understood foundations aligned with business strategy that enable self-service.
- Champion the overall strategy for data governance, security, privacy, quality, and retention in line with business policies.
- Own and document data pipelines and data lineage.
- Identify, document, and promote best practices.




- Support and maintain the analytics tech ecosystem (data warehouse, ETL, and BI tools).

Requirements

- 8+ years of experience in data management — data integration, modeling, optimization, data quality, or related data engineering areas.
- 4+ years working in cross-functional teams, collaborating with business stakeholders in Sales or Finance on departmental/multi-departmental data management and analytics initiatives involving product and business system data.
- Solid experience working with Sales, Finance, and product usage data.
- Expertise in dimensional modeling, data warehouse scaling/optimization, performance tuning, and ETL pipelines.
- Deep understanding of both relational and big data systems.
- Strong problem-solving and interpersonal skills, with the ability to make sound, complex decisions in a fast-paced technical environment.
- Ability to work across multiple areas: pipeline ETL, data modeling & design, and complex SQL.
- Excellent written and verbal communication, able to collaborate with both technical and business partners.
- Robust grasp of trade-offs and the ability to navigate between big-picture strategy and implementation detail.

Preferred

- Prior experience with Airflow.
- Hands-on experience with data warehouse technologies (Snowflake, Redshift) and big data technologies (Hadoop, Hive, Spark).
- Proficiency in Python or similar programming languages.
- Passion for data technologies broadly — SQL, NoSQL, MPP databases, etc.

📌 Senior Data Engineer (Secunderabad)
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