Platform Data Engineering - Lead

Company Description

Merkle, a dentsu company, is a leading data-driven customer experience management enterprise specializing in delivering unique, personalized customer experiences across platforms and devices. With over 30 years of experience, Merkle partners with Fortune 1000 companies and non-profit organizations to optimize their customer portfolios. Its expertise in data, technology, and analytics enables it to gain insights into consumer behavior, driving hyper-personalized marketing strategies. Merkle's consulting, creative, media, analytics, data, identity, CX/commerce, technology, and loyalty & promotions capabilities combine to drive improved marketing results and a competitive edge. With over 14,000 employees, Merkle is headquartered in Columbia, Maryland, with more than 50 additional offices worldwide. Its innovative solutions enable brands to build meaningful customer relationships and enhanced customer experience.

Job Description

Total Experience : 7 to 9 Years

Must Have Skills:

• Overall, 8 + Yrs. of experience in ETL and Data warehousing.
• 3 – 6+ Yrs. of working experience on ETL tools especially Apache Airflow.
• Implemented data pipelines, transformations and workflows using Apache Airflow.
• Scripting language viz Python, Shell Scripting.
• Strong understanding of different data warehouse schema designs, data model design and documentation.
• SQL Skills.
• Experience with relational and non-relational databases: PostgreSQL, MySQL, Redshift, Snowflake, Elastic search, MongoDB etc.

Good to have Skills:

• Query Optimization and Table design.
• Experience with Power BI or other data visualization tools preferred
• Experience using AWS services such as S3, Redshift, Lambda, RDS
• Strong expectation-setting on required effort/duration to reliably deliver work to meet client deadlines.

Key Responsibilities:

• Perform data loads and optimize data for extraction and reporting.
• Assist with discovery of data requirements to ensure proper data collection and plan/roadmap the analysis.
• Create and maintain complex data pipelines that support high-volume, high-dimensionality data from varying sources using a variety of tools and ETL techniques.
• Maintain complex databases by performing appropriate database management functions (e.g., maintain space availability, rebuilds indexes, file cleanup, runs utilities to check database integrity) to ensure optimum capacity and application performance.
• Produce and maintain data pipelines in support of client and internal reporting needs.
• Support development of client facing documentation such as a comprehensive data dictionary and data model documentation.
• Establish and maintain data models in support of operational reports, dashboards, and scorecards for internal and external clients.

Qualifications

• Experience with ETL tooling especially Apache Airflow
• Skills in programming languages such as Python a plus
• Strong understanding of different data warehouse schema designs, data model design and documentation, as well as query optimization
• Expert SQL Skills. Experience with relational and non-relational databases: PostgreSQL, MySQL, Redshift, Snowflake, Elastic search, MongoDB), table design and query optimization for each specific platform
• Experience with Power BI or other data visualization tools preferred
• Experience using AWS services such as S3, Redshift, Lambda, RDS
• Strong expectation-setting on required effort/duration to reliably deliver work to meet client deadlines.

Additional Information

1. Communication
2. Learnability
3. Teamwork
4. Result Orientation
5. Problem Solving