Requirements
- Assessments of existing data components
- Performing POCs
- Consulting to the stakeholders
- Proposing end to end solutions to an enterprise's data specific business problems, and taking care of data collection, extraction, integration, cleansing, enriching and data visualization
- Ability to design large data platforms to enable Data Engineers, Analysts & scientists
- Strong exposure to different Data architectures, data lake & data warehouse
- Define tools & technologies to develop automated data pipelines, write ETL processes, develop dashboard & report and create insights
- Continually reassess current state for alignment with architecture goals, best practices and business needs
- DB modeling, deciding best data storage, creating data flow diagrams, maintaining related documentation
- Taking care of performance, reliability, reusability, resilience, scalability, security, privacy & data governance while designing a data architecture
- Apply or recommend best practices in architecture, coding, API integration, CI/CD pipelines
- Coordinate with data scientists, analysts, and other stakeholders for data-related needs
- Help the Practice grow by mentoring junior Practice members, leading initiatives, leading Data Offerings
- Provide thought leadership by representing the Practice / Organization on internal / external platforms
- Translate business requirements into data requests, reports and dashboards
- Strong Database & modeling concepts with exposure to SQL & NoSQL Databases
- Strong data architecture patterns & principles, ability to design secure & scalable data lakes, data warehouse, data hubs, and other event-driven architectures
- Expertise in designing and writing ETL processes in Python / Java / Scala
- Understanding of Hadoop framework
- Exposure to PySpark, Spark, Storm, HDFS, Hive
- Strong hands-on experience with either Databricks or Snowflake; experience with both is desirable
- Knowledge of Master Data management and related tools
- Strong exposure to data security and privacy regulations (GDPR, HIPAA) and best practices
- Skilled in ensuring data accuracy, consistency, and quality
- Experience with the AWS/Azure/GCP data engineering services
- Knowledge of AWS services viz., AWS S3, Redshift, Lambda, DynamoDB, EMR, Glue, Lakeformation, Athena, Quicksight, RDS, Kinesis, Managed Kafka, API Gateway, CloudWatch
- Knowledge of Azure services viz., ADF, Data Catalog, Databricks, Azure Synapse Analytics, ADLS Gen2, Azure Devops
- Ability to implement data validation processes and establish data quality standards
- Experience in Linux
- Proficiency in data visualization tools like Tableau, Power BI or similar to create meaningful insights
Nice to Have
- Experience working with data ingestion tools such as Fivetran, stitch, or Matillion
- AWS IOT solutions
- Apache NiFi, Talend, Informatica
- Exposure to AI / ML technologies
Benefits
- Career growth and development
- Physical and mental wellbeing: trimester in annual cycle focused on wellbeing
- Fitness offerings
- Mental health plans (country-dependent)
- Unlimited PTO
- 100% 3Pillar funded medical and dental coverage for employees and their dependents
- Company paid disability and life insurance
- Generous Parental Leave
- Living our value for Intrinsic Dignity as an equal opportunity employer
