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Engineering Manager_Data Engineer

2 months ago

bangalore, India HashedIn by Deloitte Full time
Overview:
As an Engineering Manager with a focus on Data Engineering, you will play a pivotal role in bridging the gap between business, technology, and project management. You will be responsible for architecting and designing scalable data solutions, leading engineering teams to deliver high-quality data products, and collaborating with clients to understand their requirements and provide technical guidance. This role requires a deep understanding of data engineering, cloud platforms, and modern data architecture patterns.
Location: Bangalore, Hyderabad, Chennai, Mumbai, Pune, Gurgaon, Kolkata
Key Responsibilities:
Architect and design scalable data solutions using industry-standard technologies.
Lead engineering teams to deliver high-quality data products on time and within budget.
Collaborate with clients to understand their requirements and provide technical guidance.
Own end-to-end technical delivery of data engineering projects.
Develop and guide the team to design reusable wrappers, templates, and frameworks.
Maintain a high-quality technical bar and actively work to improve quality.
Understand and help the team follow Agile processes.
Actively negotiate, manage, and deliver promised release scope considering technical trade-offs.
Serve as the Single Point of Contact (SPOC) for any engineering-related issues.
Maintain expert-level knowledge of tools and automated processes for efficiency and robust engineering practices.
Strive to improve the efficiency and sustainability of processes and product designs.
Communicate technical information to both technical and non-technical stakeholders, including investors and potential customers.
General Skills:
Proficiency in Spark with Python or Scala.
Strong understanding of databases and data warehousing concepts.
Experience with cloud platforms such as AWS, Azure, and GCP (cloud-certified candidates are preferred).
Expertise in building resilient and scalable ETL pipelines and batch data processing.
Expertise in designing cost effective data lakes and data warehousing solutions.
Familiarity with data modernization use-cases
Experience with data streaming technologies and patterns.
Experience in data analytics and data story-telling.
Special Skills:
Expertise in Spark, Kafka and Databricks (certified candidates are preferred).
Expertise in building Cloud Data engineering solutions
Strong understanding of architecture patterns related to data engineering.
Strong understanding of complex business problems to ensure projects are leveraging the appropriate technology and the technical design.
Enterprise-scale technical experience with cloud and hybrid infrastructures, architecture designs, database migrations, and technology management.
Experience in moving data from on-premises data platforms to cloud and designing cloud native data warehouse platform.
Experience working with transactional, temporal, time series, and structured and unstructured data.
Big Data and Data Warehouses including AWS Glue, AWS EMR, GCP Dataflow, GCP Dataproc, Azure Synapse Analytics (formerly Azure SQL DW), Snowflake, GCP’s Big Query, AWS Redshift, Azure Data Lake, Azure Data Explorer, Azure Data Bricks
Advanced Analytics including Azure Synapse Analytics, data visualization tools (i.e. PowerBI, Tableau)
Experience with cloud infrastructure, storage optimization and query optimizations.
Experience in delivering/managing lifecycle of software/services using DevOps/MLOps.
Proficiency in data modeling and design, including SQL development and database administration.
Experience with cloud platforms, such as Azure, AWS, GCP to manage and integrate data systems.
Knowledge of big data developments and technology architectures.
Familiarity with data security measures and compliance regulations.
Ability to design and model database, data warehouse, and data flow infrastructures.
Understanding of data integration and the tools to manage data flow.
Preferred Qualifications:
Bachelor's or Master’s degree in Computer Science, a related technical discipline, or equivalent practical experience.
Overall industry experience of 6-10 years, with 2-4 years of experience in technical leadership and managing technology team members.
Proven experience in handling large-scale data projects.
Strong leadership and communication skills.
Relevant cloud certifications (AWS, Azure, GCP).
Experience in designing, implementing, reviewing, and delivering complex systems.
Proficiency with Agile/Scrum or similar collaborative tools.
Ability to prioritize tasks and work under dynamic requirements and deadlines.
Highly data-driven with attention to detail.
Leadership capabilities, with the ability to mentor and motivate team members to achieve project goals.